Autonomously delivering items to corresponding delivery locations proximate a delivery route

ABSTRACT

Various systems and methodologies may be utilized to determine whether a particular shipment/item is eligible for delivery between a manual delivery vehicle and a final destination location via an autonomous delivery vehicle. To ensure autonomous deliveries are performed in a resource effective manner, shipments/items deemed eligible for autonomous delivery may be vetted by comparing the destination for the autonomous delivery shipment/item against one or more manual delivery destinations (serviced by the manual delivery vehicle operator), and ultimately identifying an optimal launch location for the autonomous delivery vehicle to leave the manual delivery vehicle to complete the autonomous delivery. If the autonomous delivery location does not satisfy applicable autonomous delivery criteria, the autonomous delivery shipment/item may be reclassified for manual delivery by the manual delivery vehicle operator.

RELATED APPLICATION

This patent application claims the benefit of and is a continuation ofU.S. patent application Ser. No. 15/621,140, filed Jun. 13, 2017 andentitled “AUTONOMOUSLY DELIVERING ITEMS TO CORRESPONDING DELIVERYLOCATIONS PROXIMATE A DELIVERY ROUTE.” This application is herebyexpressly incorporated by reference in its entirety.

BACKGROUND

As autonomous delivery hardware, such as flying delivery drones, becomesmore prevalent, the focus of innovation has generally been on theautonomous delivery hardware itself and guidance algorithms fordirecting autonomous delivery vehicles to intended destinations.Specifically, the autonomous delivery industry has, to date, focused oninnovating locomotion mechanisms, power generation and storage devices,lift capacity of the delivery hardware, travel range of the deliveryhardware, guidance and obstacle avoidance algorithms, and/or the like.

However, efficient item delivery requires a consideration of otheraspects beyond hardware and navigation concerns. For example, selectingan appropriate delivery time and delivery route may significantly impactdelivery efficiency, and accordingly additional innovation is needed toenable autonomous vehicles to efficiently deliver items to variouslocations.

BRIEF SUMMARY

Various embodiments are directed to systems and methods for establishingautonomous delivery vehicle routes based on established manual deliveryvehicle routes to enable efficient operation of both manual deliveryvehicles and autonomous delivery vehicles. To minimize autonomousvehicle travel distances, the autonomous vehicles may be configured tolaunch from the manual delivery vehicles as the manual delivery vehicletraverses a pre-established vehicle route. Accordingly, variousembodiments are configured to determine optimal launch locations fromthe manual delivery vehicle to minimize travel distances for theautonomous delivery vehicles and to minimize travel delays to the manualdelivery vehicle while the autonomous delivery vehicle is on a deliveryassignment.

Various embodiments are directed to an autonomous vehicle item deliverysystem for autonomously delivering at least one item to a destinationlocation. In certain embodiments, the system comprises: a manualdelivery vehicle operable by a vehicle operator, wherein the manualdelivery vehicle is configured to traverse an assigned manual deliveryvehicle route between a plurality of manual delivery locations; anautonomous delivery vehicle (e.g., an unmanned aerial vehicle)configured for autonomously transporting at least one item between themanual delivery vehicle and an autonomous delivery location; and acomputing entity comprising one or more memory storage areas and one ormore hardware processors. In certain embodiments, the one or morehardware processors are configured to: receive item data for the atleast one item identified for autonomous delivery, wherein the item dataidentifies an autonomous delivery location for the at least one item;determining, based at least in part on the item data, a launch locationalong the manual delivery vehicle route for the at least one item; andwherein the autonomous vehicle is configured to depart the manualdelivery vehicle at the launch location to deliver the at least one itemto the autonomous delivery location.

In certain embodiments, the manual delivery vehicle comprises an onboardcomputing entity configured to monitor the location of the manualdelivery vehicle relative to the launch location, and wherein theonboard computing entity of the manual delivery vehicle is configured totransmit a signal to the autonomous delivery vehicle when the manualdelivery vehicle is at least substantially located at the launchlocation. The launch location may be a manual delivery location for asecond item.

Moreover, in certain embodiments, the autonomous delivery vehicle isconfigured to receive manual delivery vehicle location data indicativeof a current location of the manual delivery vehicle; and the autonomousdelivery vehicle is configured to, based at least in part on the manualdelivery vehicle location data, return to the manual delivery vehicleafter completing delivery of the at least one item to the autonomousdelivery location.

Certain embodiments are directed to a method for delivering at least oneitem from a manual delivery vehicle to a destination location via anautonomous delivery vehicle. The method may comprise steps for:receiving, via a computing entity, item data for a plurality of items tobe delivered to corresponding delivery locations at least in part via adelivery vehicle; electronically classifying, based at least in part onthe item data, each of the plurality of items as one of manual-deliveryeligible or autonomous-delivery eligible, wherein manualdelivery-eligible items are eligible for final delivery between thedelivery vehicle and corresponding manual delivery locations by adelivery vehicle operator and autonomous-delivery eligible items areeligible for final delivery between the delivery vehicle andcorresponding autonomous delivery locations by an autonomous vehicle;determining whether at least one autonomous delivery-eligible itemsatisfies autonomous delivery criteria by: comparing a destinationlocation for the at least one autonomous delivery-eligible item againstthe delivery locations corresponding to the manual delivery eligibleitems; and responsive to determining that the autonomous deliverycriteria is satisfied: identifying at least one manual delivery locationas a launch location for the autonomous vehicle to depart the deliveryvehicle for final delivery to the destination location; monitoring thelocation of the delivery vehicle relative to the launch location; andupon detecting that the delivery vehicle is at the launch location,causing the autonomous vehicle to depart from the delivery vehicle todeliver the at least one autonomous-delivery eligible item to thedestination location. Upon determining that the autonomous deliverycriteria is not satisfied, certain embodiments comprise steps forreclassifying the at least one autonomous-delivery eligible item to be amanual-delivery eligible item.

In certain embodiments, the autonomous delivery criteria defines ageographical area surrounding the destination location and a minimumpresence time that the delivery vehicle must be present within thegeographical area. In such embodiments, determining whether the at leastone autonomous delivery-eligible item satisfies autonomous deliverycriteria comprises: comparing the manual delivery locations against thegeographical area to determine whether one or more of the manualdelivery locations are within the geographical area; determining anestimated delivery time for each manual-delivery eligible shipmentdestined to be delivered to a manual delivery location located withinthe geographical area; comparing the cumulative estimated delivery timefor all manual-delivery eligible shipments destined to be delivered tocorresponding manual delivery locations located within the geographicalarea against the minimum presence time; and responsive to determiningthat the cumulative estimated delivery time for all manual-deliveryeligible shipments destined to be delivered to corresponding manualdelivery locations located within the geographical area satisfies theminimum presence time, identifying at least one of the manual deliverylocations located within the geographical area to be the launchlocation. In certain embodiments, determining an estimated delivery timefor each manual-delivery eligible shipment comprises: retrieving, from alocation database, a location profile for each manual delivery locationlocated within the geographical area; and retrieving, from the locationprofile corresponding to each manual delivery location located withinthe geographical area, an estimated delivery time for deliveries to themanual delivery location. In certain embodiments, the cumulativeestimated delivery time for all manual-delivery eligible shipmentscomprises the estimated delivery time for deliveries to each manualdelivery location within the geographical area and the estimated traveltime for the delivery vehicle to travel between each of the manualdelivery locations within the geographical area. In certain embodiments,the delivery criteria defines a first geographical area surrounding thedestination location and an associated first minimum presence time, anda second geographical area surrounding the destination location and anassociated second minimum presence time, wherein the second geographicalarea is larger than the first geographical area and the second minimumpresence time is longer than the first minimum presence time.

In various embodiments, the autonomous delivery criteria defines ageographical area surrounding a manual delivery location, anddetermining whether the at least one autonomous delivery-eligible itemsatisfies autonomous delivery criteria comprises: comparing the at leastone autonomous delivery location against the geographical area todetermine whether the at least one autonomous delivery location iswithin the geographical area; and responsive to determining that theautonomous delivery location is within the geographical area,identifying the manual delivery location to be the launch location. Invarious embodiments, the geographical area is defined based at least inpart on a maximum estimated round trip time for an autonomous vehicle todeliver an item to the autonomous delivery location from the manualdelivery location.

In various embodiments, the autonomous delivery criteria indicates thatautonomous delivery is available to a predefined listing of deliverylocations, and determining whether the at least one autonomousdelivery-eligible item satisfies autonomous delivery criteria comprises:comparing the at least one autonomous delivery location against thepredefined listing of delivery locations; and responsive to determiningthat the autonomous delivery location matches one of the predefinedlistings of delivery locations, identifying a manual delivery locationto be the launch location. In various embodiments, the predefinedlisting of delivery locations is identified based at least in part onone or more manual delivery locations for one or more of themanual-delivery eligible items.

In certain embodiments, the item data identifies one or more itemattributes for the corresponding item, and identifying one or more itemsas autonomous-delivery eligible comprises: comparing the one or moreitem attributes against autonomous-delivery eligibility criteria;wherein the autonomous-delivery eligibility criteria defines at leastone of: a maximum item size, a maximum item weight, a maximum itemvalue, one or more excluded item contents, a consignee approvalrequirement, or a delivery location requirement. Moreover, in certainembodiments the method further comprises steps for monitoring thelocation of the autonomous vehicle while the autonomous vehicle deliversthe at least one autonomous-delivery eligible item from the deliveryvehicle to the destination location; and upon detecting that thedelivery vehicle begins moving before the autonomous vehicle completesthe delivery of the at least one autonomous-delivery eligible item,generating an alert to the delivery vehicle operator. In variousembodiments, identifying at least one manual delivery location as alaunch location for the autonomous vehicle to depart the deliveryvehicle comprises: identifying a manual delivery location within adefined distance of the destination location, wherein the defineddistance is less than a travel range of the autonomous vehicle.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

Reference will now be made to the accompanying drawings, which are notnecessarily drawn to scale, and wherein:

FIG. 1 is a diagram of a system that can be used to practice variousembodiments of the present invention.

FIG. 2 is a schematic of a mapping computing entity in accordance withcertain embodiments of the present invention.

FIG. 3 is a schematic of a mobile computing entity in accordance withcertain embodiments of the present invention.

FIG. 4 schematically depicts a top view of an autonomous deliveryvehicle according to one or more embodiments of the present invention.

FIG. 5 schematically depicts a manual delivery vehicle and a pluralityof autonomous delivery vehicles according to one or more embodiments ofthe present invention.

FIG. 6 is a flowchart depicting various steps for establishing a dronelaunch location according to various embodiments.

FIGS. 7-9 depict example manual delivery vehicle travel paths relativeto various delivery locations according to various embodiments.

FIG. 10 illustrates example data stored in a serviceable point profileaccording to various embodiments.

FIG. 11 is a flowchart depicting various steps for establishing a dronelaunch location according to various embodiments.

FIG. 12 depicts an example manual delivery vehicle travel path relativeto various delivery locations according to various embodiments.

FIG. 13 illustrates example data stored in a serviceable point profileaccording to various embodiments.

FIG. 14 is a flowchart depicting various steps for establishing a dronelaunch location according to various embodiments.

FIG. 15 depicts an example manual delivery vehicle travel path relativeto various delivery locations according to various embodiments.

FIG. 16 illustrates example data stored in a serviceable point profileaccording to various embodiments.

DETAILED DESCRIPTION

The present disclosure more fully describes various embodiments withreference to the accompanying drawings. It should be understood thatsome, but not all embodiments are shown and described herein. Indeed,the embodiments may take many different forms, and accordingly thisdisclosure should not be construed as limited to the embodiments setforth herein. Rather, these embodiments are provided so that thisdisclosure will satisfy applicable legal requirements. Like numbersrefer to like elements throughout.

I. OVERVIEW

Various embodiments are directed to systems and methods for autonomouslydelivering items to corresponding destination locations locatedproximate a delivery route for a manual delivery vehicle (e.g., adelivery vehicle operated by a human; an autonomous base deliveryvehicle transporting a human delivery personnel who completes variousdeliveries; an autonomous base delivery vehicle transporting a pluralityof smaller, auxiliary autonomous vehicles (referred to herein simply asautonomous vehicles); and/or the like). The manual delivery vehicleserves as a launching point for the autonomous delivery vehicles, andaccordingly various embodiments are configured to determine an optimallaunching time/location for the autonomous vehicle to depart from themanual delivery vehicle, relative to the location of the manual deliveryvehicle along its route. The optimal launching location may beestablished based at least in part on the overall travel range of theautonomous vehicle, the estimated travel time for the autonomous vehicleto reach the destination location and to return to the manual deliveryvehicle, the estimated amount of time the manual delivery vehicle islikely to remain at a particular location (e.g., a manual deliverydestination), and/or the like. Accordingly, the launch location for theautonomous vehicle may be established to minimize travel delays of themanual delivery vehicle while ensuring the autonomous vehicle is able tocomplete an assigned delivery task and to return to the manual deliveryvehicle.

In various embodiments, launch locations are selected from a variety ofpotential launch locations within a threshold distance away from anintended autonomous delivery destination location. The launch locationsmay be selected based on the amount of time the manual delivery vehicleis expected to remain within the threshold distance of the intendedautonomous delivery destination location (e.g., while a delivery vehicleoperator completes manual deliveries to locations within the thresholddistance), the estimated amount of time to complete the autonomousdelivery, and/or the like.

In certain embodiments, launch locations may be predesignated, andaccordingly autonomous delivery may be available only for destinationlocations located within a predefined distance of a particularpredesignated launch location. For example, certain manual deliverydestinations (e.g., office buildings, apartment building, malls, and/orother delivery destinations which are expected to require a lengthy stoptime to complete deliveries) may be indicated as predesignated launchlocations. Accordingly, autonomous delivery may be available only fordestination locations within a defined distance away from thepredesignated launch locations.

In certain embodiments, launch locations for various autonomousdeliveries may be identified based on one or more established clustersof locations, between which autonomous delivery is considered eligible.For example, neighborhoods, geofenced areas, and/or the like mayencompass a plurality of clustered destination locations, such that anyone of the destination locations within the location cluster may serveas a launch location for autonomous delivery to any other destinationlocations within the same location cluster. As just one example, afirst-visited manual delivery destination location within a locationcluster (e.g., the first residence visited by a delivery vehicleoperator within a particular neighborhood) may be designated as a launchlocation for one or more autonomous deliveries to other destinationlocations located within the same location cluster.

II. COMPUTER PROGRAM PRODUCTS, METHODS, AND COMPUTING ENTITIES

Embodiments of the present invention may be implemented in various ways,including as computer program products that comprise articles ofmanufacture. A computer program product may include a non-transitorycomputer-readable storage medium storing applications, programs, programmodules, scripts, source code, program code, object code, byte code,compiled code, interpreted code, machine code, executable instructions,and/or the like (also referred to herein as executable instructions,instructions for execution, program code, and/or similar terms usedherein interchangeably). Such non-transitory computer-readable storagemedia include all computer-readable media (including volatile andnon-volatile media).

In one embodiment, a non-volatile computer-readable storage medium mayinclude a floppy disk, flexible disk, hard disk, solid-state storage(SSS) (e.g., a solid state drive (SSD), solid state card (SSC), solidstate module (SSM)), enterprise flash drive, magnetic tape, or any othernon-transitory magnetic medium, and/or the like. A non-volatilecomputer-readable storage medium may also include a punch card, papertape, optical mark sheet (or any other physical medium with patterns ofholes or other optically recognizable indicia), compact disc read onlymemory (CD-ROM), compact disc-rewritable (CD-RW), digital versatile disc(DVD), Blu-ray disc (BD), any other non-transitory optical medium,and/or the like. Such a non-volatile computer-readable storage mediummay also include read-only memory (ROM), programmable read-only memory(PROM), erasable programmable read-only memory (EPROM), electricallyerasable programmable read-only memory (EEPROM), flash memory (e.g.,Serial, NAND, NOR, and/or the like), multimedia memory cards (MMC),secure digital (SD) memory cards, SmartMedia cards, CompactFlash (CF)cards, Memory Sticks, and/or the like. Further, a non-volatilecomputer-readable storage medium may also include conductive-bridgingrandom access memory (CBRAM), phase-change random access memory (PRAM),ferroelectric random-access memory (FeRAM), non-volatile random-accessmemory (NVRAM), magnetoresistive random-access memory (MRAM), resistiverandom-access memory (RRAM), Silicon-Oxide-Nitride-Oxide-Silicon memory(SONOS), floating junction gate random access memory (FJG RAM),Millipede memory, racetrack memory, and/or the like.

In one embodiment, a volatile computer-readable storage medium mayinclude random access memory (RAM), dynamic random access memory (DRAM),static random access memory (SRAM), fast page mode dynamic random accessmemory (FPM DRAM), extended data-out dynamic random access memory (EDODRAM), synchronous dynamic random access memory (SDRAM), double datarate synchronous dynamic random access memory (DDR SDRAM), double datarate type two synchronous dynamic random access memory (DDR2 SDRAM),double data rate type three synchronous dynamic random access memory(DDR3 SDRAM), Rambus dynamic random access memory (RDRAM), TwinTransistor RAM (TTRAM), Thyristor RAM (T-RAM), Zero-capacitor (Z-RAM),Rambus in-line memory module (RIMM), dual in-line memory module (DIMM),single in-line memory module (SIMM), video random access memory (VRAM),cache memory (including various levels), flash memory, register memory,and/or the like. It will be appreciated that where embodiments aredescribed to use a computer-readable storage medium, other types ofcomputer-readable storage media may be substituted for or used inaddition to the computer-readable storage media described above.

As should be appreciated, various embodiments of the present inventionmay also be implemented as methods, apparatus, systems, computingdevices, computing entities, and/or the like. As such, embodiments ofthe present invention may take the form of an apparatus, system,computing device, computing entity, and/or the like executinginstructions stored on a computer-readable storage medium to performcertain steps or operations. However, embodiments of the presentinvention may also take the form of an entirely hardware embodimentperforming certain steps or operations.

Embodiments of the present invention are described below with referenceto block diagrams and flowchart illustrations. Thus, it should beunderstood that each block of the block diagrams and flowchartillustrations may be implemented in the form of a computer programproduct, an entirely hardware embodiment, a combination of hardware andcomputer program products, and/or apparatus, systems, computing devices,computing entities, and/or the like carrying out instructions,operations, steps, and similar words used interchangeably (e.g., theexecutable instructions, instructions for execution, program code,and/or the like) on a computer-readable storage medium for execution.For example, retrieval, loading, and execution of code may be performedsequentially such that one instruction is retrieved, loaded, andexecuted at a time. In some exemplary embodiments, retrieval, loading,and/or execution may be performed in parallel such that multipleinstructions are retrieved, loaded, and/or executed together. Thus, suchembodiments can produce specifically-configured machines performing thesteps or operations specified in the block diagrams and flowchartillustrations. Accordingly, the block diagrams and flowchartillustrations support various combinations of embodiments for performingthe specified instructions, operations, or steps.

III. EXEMPLARY SYSTEM ARCHITECTURE

FIG. 1 provides an illustration of a system that can be used inconjunction with various embodiments of the present invention. As shownin FIG. 1, the system may include one or more vehicles (e.g., manualdelivery vehicles 100, autonomous delivery vehicles 140, and/or thelike), one or more mobile computing entities 105, one or more mappingcomputing entities 110, one or more Global Positioning System (GPS)satellites 115, one or more location sensors, one or moreinformation/data collection devices 130, one or more networks 135, oneor more location devices, one or more user computing entities (notshown), and/or the like. Each of the components of the system may be inelectronic communication with, for example, one another over the same ordifferent wireless or wired networks including, for example, a wired orwireless Personal Area Network (PAN), Local Area Network (LAN),Metropolitan Area Network (MAN), Wide Area Network (WAN), or the like.

Additionally, while FIG. 1 illustrates certain system entities asseparate, standalone entities, the various embodiments are not limitedto this particular architecture.

A. Exemplary Mapping Computing Entity

As shown in FIG. 2, in one embodiment, the mapping computing entity 110may include or be in communication with one or more processing elements305 (also referred to as processors, processing circuitry, and/orsimilar terms used herein interchangeably) that communicate with otherelements within the mapping computing entity 110 via a bus, for example.As will be understood, the processing element 305 may be embodied in anumber of different ways. For example, the processing element 305 may beembodied as one or more complex programmable logic devices (CPLDs),microprocessors, multi-core processors, coprocessing entities,application-specific instruction-set processors (ASIPs), and/orcontrollers. Further, the processing element 305 may be embodied as oneor more other processing devices or circuitry. The term circuitry mayrefer to an entirely hardware embodiment or a combination of hardwareand computer program products. Thus, the processing element 305 may beembodied as integrated circuits, application specific integratedcircuits (ASICs), field programmable gate arrays (FPGAs), programmablelogic arrays (PLAs), hardware accelerators, other circuitry, and/or thelike. As will therefore be understood, the processing element 305 may beconfigured for a particular use or configured to execute instructionsstored in volatile or non-volatile media or otherwise accessible to theprocessing element 305. As such, whether configured by hardware orcomputer program products, or by a combination thereof, the processingelement 305 may be capable of performing steps or operations accordingto embodiments of the present invention when configured accordingly.

In one embodiment, the mapping computing entity 110 may further includeor be in communication with non-volatile media (also referred to asnon-volatile storage, memory, memory storage, memory circuitry and/orsimilar terms used herein interchangeably). In one embodiment, thenon-volatile storage or memory may include one or more non-volatilestorage or memory media 310 as described above, such as hard disks, ROM,PROM, EPROM, EEPROM, flash memory, MMCs, SD memory cards, Memory Sticks,CBRAIVI, PRAM, FeRAM, RRAM, SONOS, racetrack memory, and/or the like. Aswill be recognized, the non-volatile storage or memory media may storedatabases, database instances, database management system entities,data, applications, programs, program modules, scripts, source code,object code, byte code, compiled code, interpreted code, machine code,executable instructions, and/or the like. The term database, databaseinstance, database management system entity, and/or similar terms usedherein interchangeably may refer to a structured collection of recordsor information/data that is stored in a computer-readable storagemedium, such as via a relational database, hierarchical database, and/ornetwork database.

In one embodiment, the mapping computing entity 110 may further includeor be in communication with volatile media (also referred to as volatilestorage, memory, memory storage, memory circuitry and/or similar termsused herein interchangeably). In one embodiment, the volatile storage ormemory may also include one or more volatile storage or memory media 315as described above, such as RAM, DRAM, SRAM, FPM DRAM, EDO DRAM, SDRAM,DDR SDRAM, DDR2 SDRAM, DDR3 SDRAM, RDRAM, RIMM, DIMM, SIMM, VRAM, cachememory, register memory, and/or the like. As will be recognized, thevolatile storage or memory media may be used to store at least portionsof the databases, database instances, database management systementities, data, applications, programs, program modules, scripts, sourcecode, object code, byte code, compiled code, interpreted code, machinecode, executable instructions, and/or the like being executed by, forexample, the processing element 305. Thus, the databases, databaseinstances, database management system entities, data, applications,programs, program modules, scripts, source code, object code, byte code,compiled code, interpreted code, machine code, executable instructions,and/or the like may be used to control certain aspects of the operationof the mapping computing entity 110 with the assistance of theprocessing element 305 and operating system.

As indicated, in one embodiment, the mapping computing entity 110 mayalso include one or more communications interfaces 320 for communicatingwith various computing entities, such as by communicating data, content,information, and/or similar terms used herein interchangeably that canbe transmitted, received, operated on, processed, displayed, stored,and/or the like. For instance, the mapping computing entity 110 maycommunicate with computing entities or communication interfaces of thevehicle 100, mobile computing entities 105, and/or the like.

Such communication may be executed using a wired information/datatransmission protocol, such as fiber distributed information/datainterface (FDDI), digital subscriber line (DSL), Ethernet, asynchronoustransfer mode (ATM), frame relay, information/data over cable serviceinterface specification (DOCSIS), or any other wired transmissionprotocol. Similarly, the mapping computing entity 110 may be configuredto communicate via wireless external communication networks using any ofa variety of protocols, such as GPRS, UMTS, CDMA2000, 1×RTT, WCDMA,TD-SCDMA, LTE, E-UTRAN, EVDO, HSPA, HSDPA, Wi-Fi, WiMAX, UWB, IRprotocols, Bluetooth protocols, USB protocols, and/or any other wirelessprotocol. As yet other examples, the mapping computing entity 110 may beconfigured to transmit and/or receive information/data transmissions vialight-based communication protocols (e.g., utilizing specific lightemission frequencies, wavelengths (e.g., visible light, infrared light,and/or the like), and/or the like to transmit data), to transmit data)via sound-based communication protocols (e.g., utilizing specific soundfrequencies to transmit data), and/or the like. Although not shown, themapping computing entity 110 may include or be in communication with oneor more input elements, such as a keyboard input, a mouse input, a touchscreen/display input, audio input, pointing device input, joystickinput, keypad input, and/or the like. The mapping computing entity 110may also include or be in communication with one or more output elements(not shown), such as audio output, video output, screen/display output,motion output, movement output, and/or the like.

As will be appreciated, one or more of the mapping computing entity's110 components may be located remotely from other mapping computingentity 110 components, such as in a distributed system. Furthermore, oneor more of the components may be combined and additional componentsperforming functions described herein may be included in the mappingcomputing entity 110. Thus, the mapping computing entity 110 can beadapted to accommodate a variety of needs and circumstances.

B. Exemplary User Computing Entity

In various embodiments, a user device as discussed herein may be a usercomputing entity 105. As discussed herein, the user computing entity 105may be a stationary computing device (e.g., a desktop computer, anartificial intelligence (AI) computing entity (e.g., Amazon Echo, GoogleHome, Apple HomePod, and/or the like) a server, a mounted computingdevice, and/or the like) or a mobile computing device (e.g., a PDA, asmartphone, a tablet, a phablet, a wearable computing entity, a mobileAI computing entity (e.g., Amazon Echo Dot, and/or the like) and/or thelike) having an onboard power supply (e.g., a battery). Moreover, incertain embodiments, the user computing entity 105 may be embodied as anInternet of Things (IoT) computing entity to provide various specificfunctionalities (e.g., a subset of those discussed herein). For example,the IoT computing entities may comprise a Nest thermostat, a Ring.comdoorbell, a Wemo IoT power outlet, a Phillips Hue lightbulb, and/or thelike.

FIG. 3 provides an illustrative schematic representative of a usercomputing entity 105 that can be used in conjunction with embodiments ofthe present invention. In one embodiment, the user computing entities105 may include one or more components that are functionally similar tothose of the mapping computing entity 110 and/or as described below. Aswill be recognized, user computing entities 105 can be operated byvarious parties, including residents, employees, and/or visitors of afacility. As shown in FIG. 5, a user computing entity 105 can include anantenna 412, a transmitter 404 (e.g., radio), a receiver 406 (e.g.,radio), and a processing element 408 that provides signals to andreceives signals from the transmitter 404 and receiver 406,respectively.

The signals provided to and received from the transmitter 404 and thereceiver 406, respectively, may include signaling information/data inaccordance with an air interface standard of applicable wireless systemsto communicate with various entities, such as autonomous vehicles 140,mapping computing entities 110, location devices, and/or the like. Inthis regard, the user computing entity 105 may be capable of operatingwith one or more air interface standards, communication protocols,modulation types, and access types. More particularly, the usercomputing entity 105 may operate in accordance with any of a number ofwireless communication standards and protocols. In a particularembodiment, the user computing entity 105 may operate in accordance withmultiple wireless communication standards and protocols, such as GPRS,UMTS, CDMA2000, 1×RTT, WCDMA, TD-SCDMA, LTE, E-UTRAN, EVDO, HSPA, HSDPA,Wi-Fi, WiMAX, UWB, IR protocols, Bluetooth protocols, USB protocols,and/or any other wireless protocol. As yet other examples, the usercomputing entity 105 may be configured to transmit and/or receiveinformation/data transmissions via light-based communication protocols(e.g., utilizing specific light emission frequencies, wavelengths (e.g.,visible light, infrared light, and/or the like), and/or the like totransmit data), to transmit data) via sound-based communicationprotocols (e.g., utilizing specific sound frequencies to transmit data),and/or the like.

Via these communication standards and protocols, the user computingentity 105 can communicate with various other entities using conceptssuch as Unstructured Supplementary Service information/data (US SD),Short Message Service (SMS), Multimedia Messaging Service (MMS),Dual-Tone Multi-Frequency Signaling (DTMF), and/or Subscriber IdentityModule Dialer (SIM dialer). The user computing entity 105 can alsodownload changes, add-ons, and updates, for instance, to its firmware,software (e.g., including executable instructions, applications, programmodules), and operating system.

According to one embodiment, the user computing entity 105 (e.g., amobile user computing entity 105) may include location determiningaspects, devices, modules, functionalities, and/or similar words usedherein interchangeably. For example, the user computing entity 105 mayinclude outdoor positioning aspects, such as a location module adaptedto acquire, for example, latitude, longitude, altitude, geocode, course,direction, heading, speed, UTC, date, and/or various otherinformation/data. In one embodiment, the location module can acquiredata, sometimes known as ephemeris data, by identifying the number ofsatellites in view and the relative positions of those satellites. Thesatellites may be a variety of different satellites, including LEOsatellite systems, DOD satellite systems, the European Union Galileopositioning systems, the Chinese Compass navigation systems, IndianRegional Navigational satellite systems, and/or the like. Alternatively,the location information/data may be determined by triangulating theuser computing entity's 105 position in connection with a variety ofother systems, including cellular towers, Wi-Fi access points, locationdevices, and/or the like. Similarly, the user computing entity 105(e.g., a mobile user computing entity 105) may include indoorpositioning aspects, such as a location module adapted to acquire, forexample, latitude, longitude, altitude, geocode, course, direction,heading, speed, time, date, location identifying data, and/or variousother information/data. Some of the indoor aspects may use variousposition or location technologies including RFID tags, indoor locationdevices or transmitters, Wi-Fi access points, cellular towers, nearbycomputing devices (e.g., smartphones, laptops) and/or the like. Forinstance, such technologies may include iBeacons, Gimbal proximitybeacons, BLE transmitters, Near Field Communication (NFC) transmitters,and/or the like. These indoor positioning aspects can be used in avariety of settings to determine the location of someone or something towithin inches or centimeters.

The user computing entity 105 may also comprise a user interface (thatcan include a display 416 coupled to a processing element 408) and/or auser input interface (coupled to a processing element 408). For example,the user interface may be an application, browser, user interface,dashboard, webpage, and/or similar words used herein interchangeablyexecuting on and/or accessible via the mobile computing entity 105 tointeract with and/or cause display of information. The user inputinterface can comprise any of a number of devices allowing the usercomputing entity 105 to receive data, such as a keypad 418 (hard orsoft), a touch display, voice/speech or motion interfaces, scanners,readers, or other input device. In embodiments including a keypad 418,the keypad 418 can include (or cause display of) the conventionalnumeric (0-9) and related keys (#, *), and other keys used for operatingthe user computing entity 105 and may include a full set of alphabetickeys or set of keys that may be activated to provide a full set ofalphanumeric keys. In addition to providing input, the user inputinterface can be used, for example, to activate or deactivate certainfunctions, such as screen savers and/or sleep modes. Through such inputsthe user computing entity can collect contextual information/data aspart of the telematics data.

The user computing entity 105 can also include volatile storage ormemory 422 and/or non-volatile storage or memory 424, which can beembedded and/or may be removable. For example, the non-volatile memorymay be ROM, PROM, EPROM, EEPROM, flash memory, MMCs, SD memory cards,Memory Sticks, CBRAM, PRAM, FeRAM, RRAM, SONOS, racetrack memory, and/orthe like. The volatile memory may be RAM, DRAM, SRAM, FPM DRAM, EDODRAM, SDRAM, DDR SDRAM, DDR2 SDRAM, DDR3 SDRAM, RDRAM, RIMM, DIMM, SIMM,VRAM, cache memory, register memory, and/or the like. The volatile andnon-volatile storage or memory can store databases, database instances,database management system entities, data, applications, programs,program modules, scripts, source code, object code, byte code, compiledcode, interpreted code, machine code, executable instructions, and/orthe like to implement the functions of the user computing entity 105.

C. Exemplary Autonomous Vehicle

As utilized herein, autonomous vehicles 140 may be configured fortransporting one or more shipments/items (e.g., one or more packages,parcels, bags, containers, loads, crates, items banded together, vehicleparts, pallets, drums, the like, and/or similar words used hereininterchangeably). Various autonomous vehicles 140 may be configured asdiscussed in co-pending U.S. patent application Ser. No. 15/582,129,filed Apr. 28, 2017, and incorporated herein by reference in itsentirety.

In certain embodiments, each autonomous vehicle 140 may be associatedwith a unique vehicle identifier (such as a vehicle ID) that uniquelyidentifies the autonomous vehicle 140. The unique vehicle ID may includecharacters, such as numbers, letters, symbols, and/or the like. Forexample, an alphanumeric vehicle ID (e.g., “AS445”) may be associatedwith each vehicle 100. Although the autonomous vehicles 140 arediscussed herein as comprising unmanned aerial vehicles (UAVs), itshould be understood that the autonomous vehicles may compriseground-based autonomous vehicles 140 in certain embodiments.

FIG. 4 illustrates an example autonomous vehicle 140 that may beutilized in various embodiments. As shown in FIG. 4, the autonomousvehicle 140 is embodied as a UAV generally comprising a UAV chassis 142and a plurality of propulsion members 143 extending outwardly from theUAV chassis 142 (in certain embodiments, the propulsion members aresurrounded by propeller guards 141). The UAV chassis 142 generallydefines a body of the UAV, which the propulsion members 143 (e.g.,propellers having a plurality of blades configured for rotating within apropeller guard circumscribing the propellers) are configured to liftand guide during flight. According to various embodiments, the UAVchassis 142 may be formed from any material of suitable strength andweight (including sustainable and reusable materials), including but notlimited to composite materials, aluminum, titanium, polymers, and/or thelike, and can be formed through any suitable process.

In the embodiment depicted in FIG. 4, the autonomous vehicle 140 is ahexacopter and includes six separate propulsion members 143, eachextending outwardly from the UAV chassis 142. However, as will beappreciated from the description herein, the autonomous vehicle 140 mayinclude any number of propulsion members 143 suitable to provide liftand guide the autonomous vehicle 140 during flight. The propulsionmembers 143 are configured to enable vertical locomotion (e.g., lift)and/or horizontal locomotion, as shown in the example embodiment of FIG.4, as well as enabling roll, pitch, and yaw movements of the autonomousvehicle 140. Although not shown, it should be understood that autonomousvehicles 140 may comprise any of a variety of propulsion mechanisms,such as balloon-based lift mechanisms (e.g., enabling lighter-than-airtransportation), wing-based lift mechanisms, turbine-based liftmechanisms, and/or the like.

In the illustrated embodiment, the propulsion members 143 areelectrically powered (e.g., by an electric motor that controls the speedat which the propellers rotate). However, as will be recognized, thepropulsion members 143 may be powered by internal combustion engines(e.g., alcohol-fueled, oil-fueled, gasoline-fueled, and/or the like)driving an alternator, hydrogen fuel-cells, and/or the like.

Moreover, as shown in FIG. 4, the lower portion of the UAV chassis 142is configured to receive and engage a parcel carrier 144 configured forselectively supporting a shipment/item to be delivered from a manualdelivery vehicle 100 to a delivery destination. The parcel carrier 144may define the lowest point of the autonomous vehicle 140 when securedrelative to the chassis 142 of the autonomous vehicle 140, such that ashipment/item carried by the autonomous vehicle 140 may be positionedbelow the chassis of the autonomous vehicle 140 during transit. Incertain embodiments, the parcel carrier 144 may comprise one or moreparcel engagement arms 145 configured to detachably secure ashipment/item relative to the autonomous vehicle 140. In suchembodiments, the shipment/item may be suspended by the parcel engagementarms 145 below the autonomous vehicle 140, such that it may be releasedfrom the autonomous vehicle 140 while the autonomous vehicle 140 hoversover a desired delivery destination. However, it should be understoodthat the parcel carrier 144 may have any of a variety of configurationsenabling the autonomous vehicle 140 to support a shipment/item duringtransit. For example, the parcel carrier 144 may comprise a parcel cagefor enclosing a shipment/item during transit, a parcel platformpositioned above the UAV chassis 142, and/or the like.

In certain embodiments, the parcel carrier 144 may be detachably securedrelative to the UAV chassis 142, for example, such that alternativeparcel carriers 144 having shipments/items secured thereto may bealternatively connected relative to the UAV chassis 142 for delivery. Incertain embodiments, a UAV may be configured to deliver a shipment/itemsecured within a parcel carrier 144, and return to a manual deliveryvehicle 100 where the now-empty parcel carrier 144 (due to the deliveryof the shipment/item that was previously secured therein) may bedetached from the autonomous vehicle 140 and a new parcel carrier 144having a second shipment/item may secured to the UAV chassis 142.

As indicated by FIG. 5, which illustrates an example manual deliveryvehicle 100 according to various embodiments, the autonomous vehicle 140may be configured to selectively engage a portion of the manual deliveryvehicle 100 such that the manual delivery vehicle 100 may transport theautonomous vehicle 140. For example, the UAV chassis 142 may beconfigured to engage one or more vehicle guide mechanisms securedrelative to the manual delivery vehicle 100 to detachably secure theautonomous vehicle 140 relative to the manual delivery vehicle 100 whennot delivering shipments/items. As discussed herein, the guide mechanismof a manual delivery vehicle 100 may be configured to enable anautonomous vehicle 140 to autonomously take-off from the manual deliveryvehicle 100 to initiate a delivery activity and/or to autonomously landat the manual delivery vehicle 100 to conclude a delivery activity.

Moreover, the autonomous vehicle 140 additionally comprises an onboardcontrol system (e.g., onboard computing entity) that includes aplurality of sensing devices that assist in navigating autonomousvehicle 140 during flight. For example, the control system is configuredto control movement of the vehicle, navigation of the vehicle, obstacleavoidance, item delivery, and/or the like. Although not shown, thecontrol system may additionally comprise one or more user interfaces,which may comprise an output mechanism and/or an input mechanismconfigured to receive user input. For example, the user interface may beconfigured to enable autonomous vehicle technicians to review diagnosticinformation/data relating to the autonomous vehicle 140, and/or a userof the autonomous vehicle 140 may utilize the user interface to inputand/or review information/data indicative of a destination location forthe autonomous vehicle 140.

The plurality of sensing devices are configured to detect objects aroundthe autonomous vehicle 140 and provide feedback to an autonomous vehicleonboard control system to assist in guiding the autonomous vehicle 140in the execution of various operations, such as takeoff, flightnavigation, and landing, as will be described in greater detail herein.In certain embodiments, the autonomous vehicle control system comprisesa plurality of sensors including ground landing sensors, vehicle landingsensors, flight guidance sensors, and one or more cameras. The vehiclelanding sensors may be positioned on a lower portion of the UAV chassis142 and assist in landing the autonomous vehicle 140 on a manualdelivery vehicle 100 (e.g., as shown in FIG. 5) as will be described ingreater detail herein. The vehicle landing sensors may include one ormore cameras (e.g., video cameras and/or still cameras), one or morealtitude sensors (e.g., Light Detection and Ranging (LIDAR) sensors,laser-based distance sensors, infrared distance sensors, ultrasonicdistance sensors, optical sensors and/or the like). Being located on thelower portion of the UAV chassis 142, the vehicle landing sensors arepositioned below the propulsion members 143 and have a line of sightwith the manual delivery vehicle's UAV support mechanism (FIG. 5) whenthe autonomous vehicle 140 approaches the manual delivery vehicle 100during landing.

The autonomous vehicle's one or more cameras may also be positioned onthe lower portion of the UAV chassis 142, on propeller guards 141,and/or the like. The one or more cameras may include video and/or stillcameras, and may capture images and/or video of the flight of theautonomous vehicle 140 during a delivery process, and may assist inverifying or confirming delivery of a shipment/item to a destination, aswill be described in greater detail herein. Being located on the lowerportion of the UAV chassis 142, the one or more cameras are positionedbelow the propulsion members 143 and have an unobstructed line of sightto view the flight of the autonomous vehicle 140.

The autonomous vehicle's flight guidance sensors may also be positionedon the lower portion of the UAV chassis 142. The flight guidance sensorsmay include LIDAR, LiDAR, LADAR, SONAR, magnetic-field sensors, RADARsensors, and/or the like and may be configured to “sense and avoid”objects that the autonomous vehicle 140 may encounter during flight. Forexample the flight guidance sensors 166 may be configured to detectobjects positioned around the autonomous vehicle 140 such that theautonomous vehicle 140 may determine an appropriate flight path to avoidcontact with the objects. By positioning the flight guidance sensors onthe lower portion of the UAV chassis 142, the flight guidance sensorsare positioned below the propulsion members 143 and may have anunobstructed line of sight to view the flight of the autonomous vehicle140.

Moreover, the autonomous vehicle's ground landing sensors may be coupledto the upper portion of the UAV chassis 142. For example, the groundlanding sensors may be coupled to the propulsion members 143 at theirouter perimeter on their respective propeller guards. According tovarious embodiments, the ground landing sensors are generally configuredto detect a distance between the autonomous vehicle 140 and surfacespositioned within a line of sight of the ground landing sensors. Forexample, during flight, the ground landing sensors may detect a distancebetween the autonomous vehicle 140 and a landing surface, such as theground or the roof of the manual delivery vehicle. By detecting adistance between the autonomous vehicle 140 and a landing surface, theground landing sensors may assist in the takeoff and landing of theautonomous vehicle 140. According to various embodiments, the groundlanding sensors may include SONAR sensors, LIDAR sensors, IR-Locksensors, infrared distance sensors, ultrasonic distance sensors,magnetic-field sensors, RADAR sensors, and/or the like.

In various embodiments, the control system of the autonomous vehicle 140may encompass, for example, an information/data collection devicesimilar to information/data collection device 130 discussed in referenceto a manual delivery vehicle 100 or other computing entities. Ingeneral, the terms computing entity, entity, device, system, and/orsimilar words used herein interchangeably may refer to, for example, oneor more computers, computing entities, desktop computers, mobile phones,tablets, phablets, notebooks, laptops, distributed systems, gamingconsoles (e.g., Xbox, Play Station, Wii), watches, glasses, iBeacons,proximity beacons, key fobs, radio frequency identification (RFID) tags,ear pieces, scanners, televisions, dongles, cameras, wristbands,wearable items/devices, items/devices, vehicles, kiosks, inputterminals, servers or server networks, blades, gateways, switches,processing devices, processing entities, set-top boxes, relays, routers,network access points, base stations, the like, and/or any combinationof devices or entities adapted to perform the functions, operations,and/or processes described herein.

In one embodiment, the information/data collection device 130 mayinclude, be associated with, or be in wired or wireless communicationwith one or more processors (various exemplary processors are describedin greater detail below), one or more location-determining devices orone or more location sensors (e.g., Global Navigation Satellite System(GNSS) sensors, indoor location sensors, such as Bluetooth sensors,Wi-Fi sensors, and/or the like), one or more real-time clocks, a J-Busprotocol architecture, one or more electronic control modules (ECM), oneor more communication ports for receiving information/data from varioussensors (e.g., via a CAN-bus), one or more communication ports fortransmitting/sending data, one or more RFID tags/sensors, one or morepower sources, one or more information/data radios for communicationwith a variety of communication networks, one or more memory modules,and one or more programmable logic controllers (PLC). It should be notedthat many of these components may be located in the autonomous vehicle140 but external to the information/data collection device 130.

In one embodiment, the one or more location sensors, modules, or similarwords used herein interchangeably may be one of several components inwired or wireless communication with or available to theinformation/data collection device 130. Moreover, the one or morelocation sensors may be compatible with GPS satellites 115, such as LowEarth Orbit (LEO) satellite systems, Department of Defense (DOD)satellite systems, the European Union Galileo positioning systems, theChinese Compass navigation systems, Indian Regional Navigationalsatellite systems, and/or the like. This information/data can becollected using a variety of coordinate systems, such as the DecimalDegrees (DD); Degrees, Minutes, Seconds (DMS); Universal TransverseMercator (UTM); Universal Polar Stereographic (UPS) coordinate systems;and/or the like.

As discussed herein, triangulation and/or proximity based locationdeterminations may be used in connection with a device associated with aparticular autonomous vehicle 140 and with various communication points(e.g., cellular towers, Wi-Fi access points, and/or the like) positionedat various locations throughout a geographic area to monitor thelocation of the vehicle 100 and/or its operator. The one or morelocation sensors may be used to receive latitude, longitude, altitude,heading or direction, geocode, course, position, time, locationidentifying information/data, and/or speed information/data (e.g.,referred to herein as location information/data and further describedherein below). The one or more location sensors may also communicatewith the mapping computing entity 110, the information/data collectiondevice 130, user computing entity 105, and/or similar computingentities.

In one embodiment, the ECM may be one of several components incommunication with and/or available to the information/data collectiondevice 130. The ECM, which may be a scalable and subservient device tothe information/data collection device 130, may have information/dataprocessing capability to decode and store analog and digital inputsreceived from, for example, vehicle systems and sensors. The ECM mayfurther have information/data processing capability to collect andpresent location information/data to the J-Bus (which may allowtransmission to the information/data collection device 130), and outputlocation identifying data, for example, via a display and/or otheroutput device (e.g., a speaker).

As indicated, a communication port may be one of several componentsavailable in the information/data collection device 130 (or be in or asa separate computing entity). Embodiments of the communication port mayinclude an Infrared information/data Association (IrDA) communicationport, an information/data radio, and/or a serial port. The communicationport may receive instructions for the information/data collection device130. These instructions may be specific to the vehicle 100 in which theinformation/data collection device 130 is installed, specific to thegeographic area and/or serviceable point to which the vehicle 100 willbe traveling, specific to the function the vehicle serves within afleet, and/or the like. In one embodiment, the information/data radiomay be configured to communicate with a wireless wide area network(WWAN), wireless local area network (WLAN), wireless personal areanetwork (WPAN), or any combination thereof. For example, theinformation/data radio may communicate via various wireless protocols,such as 802.11, general packet radio service (GPRS), Universal MobileTelecommunications System (UMTS), Code Division Multiple Access 2000(CDMA2000), CDMA2000 1× (1×RTT), Wideband Code Division Multiple Access(WCDMA), Time Division-Synchronous Code Division Multiple Access(TD-SCDMA), Long Term Evolution (LTE), Evolved Universal TerrestrialRadio Access Network (E-UTRAN), Evolution-Data Optimized (EVDO), HighSpeed Packet Access (HSPA), High-Speed Downlink Packet Access (HSDPA),IEEE 802.11 (Wi-Fi), 802.16 (WiMAX), ultra-wideband (UWB), infrared (IR)protocols, Bluetooth protocols (including Bluetooth low energy (BLE)),wireless universal serial bus (USB) protocols, and/or any other wirelessprotocol. As yet other examples, the communication port may beconfigured to transmit and/or receive information/data transmissions vialight-based communication protocols (e.g., utilizing specific lightemission frequencies, wavelengths (e.g., visible light, infrared light,and/or the like), and/or the like to transmit data), via sound-basedcommunication protocols (e.g., utilizing specific sound frequencies totransmit data), and/or the like.

In various embodiments, the autonomous vehicle 140 may comprise a userinterface one or more input devices and/or one or more output devicesconfigured to receive user input and/or to provide visual and/or audibleoutput to a user (e.g., a programmer; a technician, and/or the like).For example, the vehicle may comprise a touchscreen (e.g., a capacitivetouchscreen), a keyboard, a mouse, a touchpad, a display (e.g., an LCDdisplay, an LED display, a tube display, and/or the like), and/or thelike.

As discussed herein, the onboard control system of the autonomousvehicle 140 may be configured to generate and/or retrieve navigationalinstructions for the autonomous vehicle 140 to move to a particulardestination location within the facility. The onboard control system maybe configured to interpret the navigational instructions relative to adetermined location of the autonomous vehicle 140, and to providesignals to the onboard locomotion mechanisms to move the autonomousvehicle 140 along a determined route to the destination location whileavoiding obstacles detected by the one or more sensors of the controlsystem.

D. Exemplary Manual Delivery Vehicle

As discussed herein, a manual delivery vehicle 100 may be a humanoperable delivery vehicle configured for transporting a vehicleoperator, a plurality of items, and one or more autonomous vehicles 140along a delivery route. However, it should be understood that in certainembodiments, the manual delivery vehicle 100 may itself be autonomous orsemi-autonomous. In certain embodiments, an autonomous manual deliveryvehicle 100 may be configured as an autonomous base vehicle configuredto carry a plurality of items, one or more smaller, auxiliary autonomousvehicles (e.g., autonomous vehicles 140 described in detail herein), ahuman delivery personnel (e.g., who may complete various deliveries fromthe manual delivery vehicle 100 to respective destination locations),and/or the like. For example, a vehicle 100 may be a manned or anunmanned tractor, truck, car, motorcycle, moped, Segway, bicycle, golfcart, hand truck, cart, trailer, tractor and trailer combination, van,flatbed truck, vehicle, drone, airplane, helicopter, boat, barge, and/orany other form of object for moving or transporting people, UAVs, and/orshipments/items (e.g., one or more packages, parcels, bags, containers,loads, crates, items banded together, vehicle parts, pallets, drums, thelike, and/or similar words used herein interchangeably). In oneembodiment, each vehicle 100 may be associated with a unique vehicleidentifier (such as a vehicle ID) that uniquely identifies the vehicle100. The unique vehicle ID (e.g., trailer ID, tractor ID, vehicle ID,and/or the like) may include characters, such as numbers, letters,symbols, and/or the like. For example, an alphanumeric vehicle ID (e.g.,“AS445”) may be associated with each vehicle 100. In another embodiment,the unique vehicle ID may be the license plate, registration number, orother identifying information/data assigned to the vehicle 100. Invarious embodiments, the manual delivery vehicle 100 may be configuredas discussed in co-pending U.S. patent application Ser. No. 15/582,129,filed Apr. 28, 2017, and incorporated herein by reference in itsentirety.

In various embodiments, the manual delivery vehicle 100 comprises one ormore autonomous vehicle support mechanisms, as shown in FIG. 5. Theautonomous vehicle support mechanisms may be configured to enable theautonomous vehicles 140 to launch and land at the manual deliveryvehicle 100 while completing autonomous deliveries. In certainembodiments, the autonomous vehicle support mechanisms may be configuredto enable the autonomous vehicles 140 to launch and/or land while themanual delivery vehicle 100 is moving, however certain embodiments maybe configured to enable autonomous vehicle 140 launching and/or landingwhile the manual delivery vehicle 100 is stationary.

Moreover, although not shown, the interior of the manual deliveryvehicle 100 may comprise a cargo area configured for storing a pluralityof items, a plurality of autonomous vehicles 140, a plurality ofautonomous vehicle components, and/or the like. In certain embodiments,items designated for autonomous delivery may be stored in one or moreautonomously operated storage assemblies within the cargo area of themanual delivery vehicle 100. When a particular item is identified asready for delivery, the storage assembly autonomously delivers the itemto an autonomous vehicle 140 for delivery.

Moreover, the manual delivery vehicle 100 may comprise and/or beassociated with one or more computing entities, devices, and/or similarwords used herein interchangeably. For example, the manual deliveryvehicle 100 may be associated with an information/data collection device130 or other computing entities. In general, the terms computing entity,entity, device, system, and/or similar words used herein interchangeablymay refer to, for example, one or more computers, computing entities,desktop computers, mobile phones, tablets, phablets, notebooks, laptops,distributed systems, gaming consoles (e.g., Xbox, Play Station, Wii),watches, glasses, iBeacons, proximity beacons, key fobs, RFID tags, earpieces, scanners, televisions, dongles, cameras, wristbands, wearableitems/devices, items/devices, vehicles, kiosks, input terminals, serversor server networks, blades, gateways, switches, processing devices,processing entities, set-top boxes, relays, routers, network accesspoints, base stations, the like, and/or any combination of devices orentities adapted to perform the functions, operations, and/or processesdescribed herein. FIG. 2 provides a block diagram of an exemplaryinformation/data collection device 130 that may be attached, affixed,disposed upon, integrated into, or part of a vehicle 100. Theinformation/data collection device 130 may collect telematicsinformation/data (including location data) and transmit/send theinformation/data to the mobile computing entity 105, the mappingcomputing entity 110, and/or various other computing entities via one ofseveral communication methods.

In one embodiment, the information/data collection device 130 mayinclude, be associated with, or be in wired or wireless communicationwith one or more processors (various exemplary processors are describedin greater detail below), one or more location-determining devices orone or more location sensors (e.g., GNSS sensors), one or moretelematics sensors, one or more real-time clocks, a J-Bus protocolarchitecture, one or more ECMs, one or more communication ports forreceiving telematics information/data from various sensors (e.g., via aCAN-bus), one or more communication ports for transmitting/sending data,one or more RFID tags/sensors, one or more power sources, one or moreinformation/data radios for communication with a variety ofcommunication networks, one or more memory modules, and one or moreprogrammable logic controllers (PLC). It should be noted that many ofthese components may be located in the vehicle 100 but external to theinformation/data collection device 130.

In one embodiment, the one or more location sensors, modules, or similarwords used herein interchangeably may be one of several components inwired or wireless communication with or available to theinformation/data collection device 130. Moreover, the one or morelocation sensors may be compatible with GPS satellites 115, LEOsatellite systems, DOD satellite systems, the European Union Galileopositioning systems, the Chinese Compass navigation systems, IndianRegional Navigational satellite systems, and/or the like, as discussedabove in reference to the autonomous delivery vehicle. Alternatively,triangulation may be used in connection with a device associated with aparticular vehicle and/or the vehicle's operator and with variouscommunication points (e.g., cellular towers or Wi-Fi access points)positioned at various locations throughout a geographic area to monitorthe location of the vehicle 100 and/or its operator. The one or morelocation sensors may be used to receive latitude, longitude, altitude,heading or direction, geocode, course, position, time, and/or speedinformation/data (e.g., referred to herein as telematicsinformation/data and further described herein below). The one or morelocation sensors may also communicate with the mapping computing entity110, the information/data collection device 130, user computing entity105, and/or similar computing entities.

In one embodiment, the ECM may be one of several components incommunication with and/or available to the information/data collectiondevice 130. The ECM, which may be a scalable and subservient device tothe information/data collection device 130, may have information/dataprocessing capability to decode and store analog and digital inputs fromvehicle systems and sensors (e.g., location sensor). The ECM may furtherhave information/data processing capability to collect and presentcollected information/data to the J-Bus (which may allow transmission tothe information/data collection device 130).

As indicated, a communication port may be one of several componentsavailable in the information/data collection device 130 (or be in or asa separate computing entity). Embodiments of the communication port mayinclude an Infrared information/data Association (IrDA) communicationport, an information/data radio, and/or a serial port. The communicationport may receive instructions for the information/data collection device130. These instructions may be specific to the vehicle 100 in which theinformation/data collection device 130 is installed, specific to thegeographic area in which the vehicle 100 will be traveling, specific tothe function the vehicle 100 serves within a fleet, and/or the like. Inone embodiment, the information/data radio may be configured tocommunicate with WWAN, WLAN, WPAN, or any combination thereof, asdiscussed in reference to the autonomous vehicle, above.

E. Exemplary Shipment/Item

In one embodiment, a shipment/item may be any tangible and/or physicalobject. In one embodiment, a shipment/item may be or be enclosed in oneor more packages, envelopes, parcels, bags, goods, products, containers,loads, crates, items banded together, vehicle parts, pallets, drums, thelike, and/or similar words used herein interchangeably. In oneembodiment, each shipment/item may include and/or be associated with ashipment/item identifier, such as an alphanumeric identifier. Suchshipment/item identifiers may be represented as text, barcodes, tags,character strings, Aztec Codes, MaxiCodes, information/data Matrices,Quick Response (QR) Codes, electronic representations, and/or the like.A unique shipment/item identifier (e.g., 123456789) may be used by thecarrier to identify and track the shipment/item as it moves through thecarrier's transportation network and to associate a particular physicalshipment/item with an electronically stored shipment/item profile. Forexample, the shipment/item profile may be stored in a shipment/itemlevel detail database, and may store data informing various carrierpersonnel and/or delivery vehicles (e.g., autonomous vehicle 140) ofdelivery-related information/data specific to a particular shipment.Further, such shipment/item identifiers can be affixed toshipments/items by, for example, using a sticker (e.g., label) with theunique shipment/item identifier printed thereon (in human and/or machinereadable form) or an RFID tag with the unique shipment/item identifierstored therein. Such items may be referred to as “connected”shipments/items and/or “non-connected” shipments/items.

In one embodiment, connected shipments/items include the ability todetermine their locations and/or communicate with various computingentities. This may include the shipment/item being able to communicatevia a chip or other devices, such as an integrated circuit chip, RFIDtechnology, NFC technology, Bluetooth technology, Wi-Fi technology,light-based communication protocols, sound-based communicationprotocols, and any other suitable communication techniques, standards,or protocols with one another and/or communicate with various computingentities for a variety of purposes. Connected shipments/items mayinclude one or more components that are functionally similar to those ofthe mapping computing entity 110 and/or user computing entity 105 asdescribed herein. For example, in one embodiment, each connectedshipment/item may include one or more processing elements, one or moredisplay device/input devices (e.g., including user interfaces), volatileand non-volatile storage or memory, and/or one or more communicationsinterfaces. In this regard, in some example embodiments, a shipment/itemmay communicate send “to” address information/data, received “from”address information/data, unique identifier codes, locationinformation/data, status information/data, and/or various otherinformation/data.

In one embodiment, non-connected shipments/items do not typicallyinclude the ability to determine their locations and/or might not beable communicate with various computing entities or are not designatedto do so by the carrier. The location of non-connected shipments/itemscan be determined with the aid of other appropriate computing entities.For example, non-connected shipments/items can be scanned (e.g., affixedbarcodes, RFID tags, and/or the like) or have the containers or vehiclesin which they are located scanned or located. As will be recognized, anactual scan or location determination of a shipment/item is notnecessarily required to determine the location of a shipment/item. Thatis, a scanning operation might not actually be performed on a labelaffixed directly to a shipment/item or location determination might notbe made specifically for or by a shipment/item. For example, a label ona larger container housing many shipments/items can be scanned, and byassociation, the location of the shipments/items housed within thecontainer are considered to be located in the container at the scannedlocation. Similarly, the location of a vehicle transporting manyshipments/items can be determined, and by association, the location ofthe shipments/items being transported by the vehicle are considered tobe located in the vehicle 100 at the determined location. These can bereferred to as “logical” scans/determinations or “virtual”scans/determinations. Thus, the location of the shipments/items is basedon the assumption they are within the container or vehicle, despite thefact that one or more of such shipments/items might not actually bethere.

F. Exemplary Shipment/Item Profile

As noted herein, various shipments/items may have an associatedshipment/item profile, record, and/or similar words used hereininterchangeably stored in a shipment/item detail database. Theshipment/item profile may be utilized by the carrier to track thecurrent location of the shipment/item and to store and retrieveinformation/data about the shipment/item. For example, the shipment/itemprofile may comprise electronic data corresponding to the associatedshipment/item, and may identify various shipping instructions for theshipment/item, various characteristics of the shipment/item, and/or thelike. The electronic data may be in a format readable by variouscomputing entities, such as a mapping computing entity 110, a usercomputing entity 105, an autonomous vehicle control system, and/or thelike. However, it should be understood that a computing entityconfigured for selectively retrieving electronic data within variousshipment/item profiles may comprise a format conversion aspectconfigured to reformat requested data to be readable by a requestingcomputing entity.

In various embodiments, the shipment/item profile comprises identifyinginformation/data corresponding to the shipment/item. The identifyinginformation/data may comprise information/data identifying the uniqueitem identifier associated with the shipment/item. Accordingly, uponproviding the identifying information/data to the item detail database,the item detail database may query the stored shipment/item profiles toretrieve the shipment/item profile corresponding to the provided uniqueidentifier.

Moreover, the shipment/item profiles may comprise shippinginformation/data for the shipment/item. For example, the shippinginformation/data may identify an origin location (e.g., an originserviceable point), a destination location (e.g., a destinationserviceable point), a service level (e.g., Next Day Air, Overnight,Express, Next Day Air Early AM, Next Day Air Saver, Jetline, Sprintline,Secureline, 2nd Day Air, Priority, 2nd Day Air Early AM, 3 Day Select,Ground, Standard, First Class, Media Mail, SurePost, Freight, and/or thelike), whether a delivery confirmation signature is required, and/or thelike. In certain embodiments, at least a portion of the shippinginformation/data may be utilized as identifying information/data toidentify a shipment/item. For example, a destination location may beutilized to query the item detail database to retrieve data about theshipment/item.

In certain embodiments, the shipment/item profile comprisescharacteristic information/data identifying shipment/itemcharacteristics. For example, the characteristic information/data mayidentify dimensions of the shipment/item (e.g., length, width, height),a weight of the shipment/item, contents of the shipment/item, and/or thelike. In certain embodiments, the contents of the shipment/item maycomprise a precise listing of the contents of the shipment/item (e.g.,three widgets) and/or the contents may identify whether theshipment/item contains any hazardous materials (e.g., the contents mayindicate whether the shipment/item contains one or more of thefollowing: no hazardous materials, toxic materials, flammable materials,pressurized materials, controlled substances, firearms, and/or thelike).

Moreover, as will be discussed in greater detail herein, thecharacteristic information/data may identify whether the shipment/itemis eligible for autonomous delivery. The determination of whether theshipment/item is eligible for autonomous delivery may be based at leastin part on an intended recipient's preferences (e.g., provided to themapping computing entity 110 based at least in part on user inputprovided by the recipient), and/or based at least in part on variousinformation/data contained within the shipment/item profile. In variousembodiments, a computing entity associated with the item detail database(e.g., mapping computing entity 110) may be configured to update theshipment/item profile to include an indication of whether theshipment/item is eligible for autonomous delivery. In making such adetermination, the mapping computing entity 110 may be configured todetermine whether an intended recipient has expressed a preference forwhether autonomous delivery should be used to the deliver theshipment/item. For example, the mapping computing entity 110 may beconfigured to retrieve information/data from the shipment/item profilethat identifies the intended recipient, and the mapping computing entity110 may be configured to generate and transmit a query to a recipientpreference database (e.g., operated by a separate computing entityand/or by the same computing entity) determine whether the recipient hasexpressed a preference for autonomous delivery of shipments/items.Responsive to determining that the recipient has indicated thatautonomous delivery should not be utilized, the mapping computing entity110 may update the shipment/item profile to indicate that autonomousdelivery is not available for the shipment/item. However, if therecipient has indicated that autonomous delivery may be utilized, themapping computing entity 110 may continue to determine whether thecharacteristics of the particular item satisfy autonomous deliverycriteria. For example, the mapping computing entity 110 may compare theitem dimensions against dimensional criteria for autonomous delivery todetermine whether the item is sized appropriately for autonomousdelivery. For example, the dimensional criteria may identify one or moremaximum and/or minimum dimensions for items to be delivered via anautonomous vehicle 140. Due to size limitations of the autonomousvehicles 140 themselves, autonomous delivery may only be available foritems sized such that these items may be securely supported by theautonomous vehicle 140. Similarly, the mapping computing entity 110 maycompare the weight of the item against weight criteria for autonomousdelivery to determine whether the shipment/item is within an appropriateweight range to enable autonomous delivery. For example, the weightcriteria may specify a maximum and/or a minimum weight for items to bedelivered via an autonomous vehicle 140. The weight criteria may beestablished based on a weight limit of an autonomous vehicle 140, suchthat items are only eligible for autonomous delivery if the propulsionmechanisms of the autonomous vehicle 140 are capable of maneuvering thecombined weight of the autonomous vehicle 140 and the shipment/item.Finally, the mapping computing entity 110 may compare the contents ofthe shipment/item against a listing of permitted and/or excluded itemcontents to determine whether the contents of the shipment/item areeligible for autonomous delivery.

Responsive to determining that the shipment/item satisfies allapplicable autonomous delivery criteria, the mapping computing entity110 may be configured to update the shipment/item profile to indicatethat the shipment/item is eligible for autonomous delivery.

G. Exemplary Location Profile

In one embodiment, a serviceable point, serviceable point addresses,and/or similar words used herein interchangeably may be any identifiablelocation, such as one or more addresses, lockers, access points,delivery locations, parking locations, sidewalks, highways, trails,alleys, paths, walkways, streets, street segments, entrance or exitramps, roads, longitude and latitude points, geocodes, zip codes, areacodes, cities, counties, states, provinces, countries, stops (e.g., pickup stops, delivery stops, vehicle visits, stops) geofenced areas,geographic areas, landmarks, buildings, bridges, and/or otheridentifiable locations. For example, a serviceable point may be aresidential location, such as one or more homes, one or more mobilehomes, one or more apartments, one or more apartment buildings, one ormore condominiums, one or more townhomes, one or more points at suchlocations, and/or the like. The serviceable point may also be anyspecific location at a residential location (e.g., front door of aresidence, side door of a residence, and/or the like). A serviceablepoint may also be a commercial location, such as one or more stores in amall, one or more office buildings, one or more office parks, one ormore offices of an apartment complex, one or more garages, one or morelockers or access points, one or more warehouses, one or morerestaurants, one or more stores, one or more retail locations, one ormore points at such locations, and/or the like. The serviceable pointmay also be any specific location at a commercial location, e.g., (e.g.,front door of a commercial location, dock of a commercial location,and/or the like). A serviceable point may be one or more streets, one ormore street segments, one or more zones, one or more areas, one or morelatitude and/or longitude points (e.g., 33.7869128, −84.3875602), one ormore geocodes, and/or the like. A serviceable point may be anyidentifiable location. As will be recognized, a variety of approachesand techniques can be used to adapt to various needs and circumstances.In various embodiments, serviceable points may be configured asdiscussed in co-pending U.S. patent application Ser. No. 14/988,136,filed on Jan. 5, 2016, the contents of which are incorporated herein byreference in their entirety.

In various embodiments, a serviceable point profile corresponding toeach of one or more (e.g., all) serviceable points serviced by thecarrier may be created and stored in a serviceable point managementdatabase in electronic communication with the mapping computing entity110. Each serviceable point profile stored within the serviceable pointmanagement database may comprise serviceable point identifyinginformation/data that may comprise a unique combination of characters,symbols, words, and/or the like that may be utilized to identify aparticular serviceable point. In certain embodiments, the identifyinginformation/data may comprise the street address of the serviceablepoint, and may include the street number, the street name, a sub-unit(e.g., apartment number, suite number, floor number, and/or the like),the city, the state/province, a postal/zip code, and/or the like.Moreover, the identifying information/data may comprise information/dataindicative of alternative identifying information/data, if applicable.For example, if a particular location's street address changes, or ifthe particular location is commonly known by an identifier other thanthe street address, the serviceable point profile may compriseinformation/data identifying the previous and/or alternative locationidentifier for the serviceable point. In certain embodiments, theidentifying information/data may comprise a shortened unique identifierthat may be utilized to identify a particular serviceable point withoututilizing an entire street address. For example, the shortened uniqueidentifier may comprise a unique character string, a unique symboland/or string of symbols, and/or the like.

Moreover, in various embodiments, each serviceable point profileadditionally comprises a geocode for each of the associated serviceablepoint (e.g., a geocode established by one or more user computingentities 105 (e.g., mobile devices) while the user computing entity 105is physically located at the serviceable point). As a specific example,a serviceable point profile may identify one or more preferred deliverylocations for shipments/items to be delivered to a particular deliveryaddress (e.g., a geocode accurately identifying the location of thefront porch of a particular residence). In various embodiments, theserviceable point profile may identify a first delivery location at thecorresponding delivery address for manual deliveries (e.g., deliveriesmade by a carrier employee should be placed on a front porch of theaddress) and/or may identify a second delivery location at thecorresponding delivery address for autonomous deliveries (e.g.,deliveries made by an autonomous UAV should be deposited on asecond-story balcony of the address). Such data, including theinformation/data indicating the preferred serviceable point indicatorsand/or the alternative serviceable point indicators, may be utilized bythe mapping computing entity 110 to match a particular serviceable pointindicator provided on a shipment/item received by the carrier to one ormore appropriate serviceable point profiles. In certain embodiments, theserviceable point profile may comprise one or more images of theserviceable point. For example, the serviceable point profile maycomprise a street-view of the serviceable point, and/or one or moreclose-up views of particular preferred delivery locations for theserviceable point.

Moreover, each serviceable point profile may comprise information/dataindicative of one or more linked serviceable points at geographicallydistinct locations. The linked serviceable points may be identified ineach serviceable point profile based on a determination that autonomousdelivery may be achieved between the serviceable point associated withthe profile and the linked serviceable point, as discussed in greaterdetail below. The linked serviceable points to be associated with aparticular serviceable point profile may be identified based at least inpart on historical, real-time, and/or predictive information/data (e.g.,historical information/data indicative of the distance between addressesand/or the elapsed time between deliveries (e.g., manual deliveries,autonomous deliveries, and/or the like to multiple addresses). Invarious embodiments, the one or more linked serviceable points may beserviceable points eligible for autonomous delivery while a manualdelivery vehicle 100 is located at the serviceable point associated withthe serviceable point profile. Alternatively, the linked serviceablepoints may be serviceable points at which a manual delivery vehicle 100must be located to enable autonomous delivery to the serviceable pointassociated with the serviceable point profile. Accordingly, in certainembodiments the serviceable point profile may identify at least twodiscrete listings of linked serviceable points, including a listidentifying linked serviceable points to which autonomous delivery isavailable while the manual delivery vehicle 100 is physically located atthe serviceable point, and a list identifying linked serviceable pointsfrom which autonomous delivery is available to the serviceable pointwhile the manual delivery vehicle 100 is physically located at a linkedserviceable point. FIGS. 10, 13, and 16, discussed in greater detailbelow, illustrate example information/data that may be stored in aserviceable point profile.

In various embodiments, upon receipt of information/data indicating thata shipment/item is scheduled to be delivered to a particular destinationserviceable point, the mapping computing entity 110 may be configured todetermine whether the shipment/item is eligible for autonomous delivery(e.g., based on information/data stored within a shipment/item profileassociated with the shipment/item), and/or whether other existingshipments/items are eligible for autonomous delivery based on theinclusion of a stop to deliver the shipment/item along a delivery route.

Accordingly, the one or more mapping computing entities 110 may firstidentify the corresponding serviceable point profile (e.g., storedwithin the one or more serviceable point management databases) for theparticular destination serviceable point. In various embodiments,identifying an appropriate serviceable point profile for a particularshipment/item may comprise steps for obtaining information/dataindicative of a destination for a shipment/item (e.g., by querying ashipment/item level detail database, by scanning an indicia on thepackage, and/or by receiving user input). Upon identifying thedestination for the shipment/item, the serviceable point managementdatabase may be queried to identify a serviceable point profilecorresponding to the destination of the shipment/item. The mappingcomputing entity 110 may then retrieve information/data associated withthe serviceable point profile to ascertain whether a shipment/itemdestined for the serviceable point is eligible for autonomous delivery.

In various embodiments, the serviceable point profiles may compriseinformation/data indicative of one or more estimated elapsed times tocomplete a delivery at the serviceable point. The estimated elapsed timeto complete a delivery at the serviceable point may be determined basedon historical data, and may represent an average amount of time to makea delivery at the serviceable point. In certain embodiments, the amountof time to make a delivery may be identified as the elapsed time betweenwhen the manual vehicle's engine is turned off to enable the vehicleoperator to disembark and complete the delivery and when the vehicle'sengine is then turned on to enable the vehicle operator to leave thedelivery location. Accordingly, the estimated amount of time to completea delivery at a serviceable point comprises the sum of the estimatedamount of time for the driver to unbuckle his/her seatbelt (afterturning off the engine), get out of a driver's seat, retrieve ashipment/item to be delivered, disembark from the vehicle, transport theshipment/item from the vehicle to a delivery point at the destinationlocation (e.g., from the vehicle to the front porch of the deliverylocation), to request and obtain a delivery signature (if applicable),to return to and board the vehicle, to sit in the driver's seat, tobuckle the driver's seat belt (before turning on the engine), and toturn on the vehicle's engine.

To establish the estimated elapsed delivery time, a computing entity(e.g., mapping computing entity 110) may store and retrieve historicaldelivery information/data indicative of historical deliveries to theparticular serviceable point. The mapping computing entity 110 mayretrieve information/data indicative of the amount of time a vehicle'sengine is turned off while a delivery vehicle operator makes a deliveryto the destination location. In various embodiments, the mappingcomputing entity 110 may retrieve historical vehicle telematicsinformation/data and/or service information/data indicative of an amountof time to complete deliveries at various locations from one or morefleet management systems, such as those described in U.S. Pat. No.9,208,626, the contents of which is incorporated herein by reference inits entirety.

In various embodiments, a serviceable point profile may comprise aplurality of elapsed delivery time estimates for various possibledelivery scenarios to the serviceable point. For example, theserviceable point profile may comprise a chart showing various elapseddelivery time estimates corresponding to various delivery scenarios. Asa specific example, the elapsed delivery time estimate chart maycomprise (1) a delivery time estimate for regular, no-signature requireddeliveries, (2) a delivery time estimate for heavy (e.g., over 70 lb)deliveries, (3) a delivery time estimate for signature requireddeliveries, and/or the like. Accordingly, when retrievinginformation/data regarding the estimated elapsed time to complete anupcoming delivery as discussed herein, the mapping computing entity 110may be configured to retrieve a delivery estimate corresponding to thedelivery type for the upcoming delivery.

IV. EXEMPLARY SYSTEM OPERATION

With reference to FIGS. 6-16, various embodiments establish autonomousdelivery eligibility for various shipments/items in real-time, while afinal delivery route is established for shipments/items to be deliveredto associated destination locations (e.g., serviceable points). Certainembodiments establish final autonomous delivery eligibility based on adetermination of whether an established delivery route passes within anestablished proximity to an autonomous delivery location, whether anestablished delivery route visits one or more serviceable points linkedfor autonomous delivery to a different serviceable point, whether anestablished delivery route causes a manual delivery vehicle 100 to belocated within a particular geographical area for a threshold period oftime, and/or the like. Such concepts are discussed in greater detailherein.

A. Determining Autonomous Delivery Eligibility based on AutonomousDelivery Destination Locations

In various embodiments, determining whether one or more items may bedelivered autonomously may be based at least in part on the location ofthe prospective autonomous delivery location (e.g., serviceable point)relative to the location of an established manual delivery vehicle routeand/or the location of one or more deliveries on the ordered listing ofdeliveries to be completed by the manual delivery vehicle 100. Asdiscussed in reference to FIGS. 6-9, autonomous delivery eligibility maybe established for autonomous delivery destinations if a manual deliveryvehicle route passes within a defined distance (e.g., linear distance)of the autonomous delivery location and remains within the defineddistance for at least a threshold period of time to enable an autonomousvehicle 140 to depart from the manual delivery vehicle 100, to completethe delivery, and to return to the manual delivery vehicle 100 while themanual delivery vehicle 100 remains within the defined distance. Incertain embodiments, delivery locations existing within the defineddistance of the autonomous delivery location may be stored in theserviceable point profile corresponding to the autonomous deliverylocation as linked serviceable points.

FIG. 6 is a flowchart showing an example method for determining whetherautonomous delivery is available for various shipments/items, and FIGS.7-9 provide schematic illustrations of various scenarios that may arisefrom the methodology shown in the flowchart of FIG. 6.

As shown at Block 601 of FIG. 6, an example method for establishingautonomous delivery eligibility begins by identifying shipments/itemidentified as autonomous-delivery eligible. These shipments may beidentified based on information/data stored in a correspondingshipment/item profile (e.g., an indicator stored therein providinginformation/data regarding whether the shipment/item satisfies the oneor more criteria for establishing autonomous delivery eligibility forthe shipments/items). Identifying the shipments/items as autonomousdelivery eligible may thus comprise steps for querying the item detaildatabase to identify those shipment/item profiles indicating that thecorresponding shipments/items are eligible for autonomous delivery. Incertain embodiments, a mapping computing entity 110 querying the itemdetail database may populate a listing of autonomous delivery eligibleshipments/items for further analysis in determining whether theseshipments/items may be delivered autonomously from a manual deliveryvehicle 100 traversing an established vehicle route.

A manual delivery vehicle route (e.g., an ordered listing of deliveriesand/or a predefined travel path for a manual delivery vehicle) may beestablished prior to determining whether the autonomous deliveryeligible shipments/items may be delivered autonomously, as indicated atBlock 602 of FIG. 6. The manual delivery vehicle routes may beestablished based at least in part on the relative locations of manualdeliveries to be delivered by a particular manual deliver vehicle 100(and the associated manual delivery vehicle operator). In certainembodiments, the order in which the manual deliveries are scheduled tobe delivered may be optimized to minimize the amount of resourcesconsumed by the vehicle and/or vehicle operator while completing thedelivery route. For example, the manual delivery vehicle route may beoptimized to minimize an estimate fuel usage by the vehicle, anestimated amount of time to complete the route, and/or the like. Incertain embodiments, a mapping computing entity 110 establishing themanual delivery vehicle route for a particular vehicle may complete theroute optimization process for a plurality of vehicle routes in theaggregate, and may delegate various delivery stops to the vehicles tominimize the total resources utilized by the plurality of manualdelivery vehicles 100 while completing all of the necessary deliverystops.

In certain embodiments, the manual delivery vehicle routes may beestablished to optimize resource usage for manual deliveries alone, andautonomous deliveries may be added thereto. However, in certainembodiments, the manual delivery vehicle routes may be established tominimize the amount of resources utilized to complete all of the manualdeliveries and the autonomous deliveries. For example, the manualdelivery vehicle route may be established having one or more autonomousdelivery stops in which the manual delivery vehicle 100 stops at apredetermined location (which may or may not correspond to a manualdelivery serviceable point) to enable the autonomous vehicles 140 tocomplete one or more deliveries while the manual delivery vehicle 100remains stationary.

The established manual delivery vehicle route may comprise an orderedlisting of deliveries to be completed by the manual delivery vehicle100, and therefore the manual delivery vehicle route may not have anestablished vehicle travel path associated therewith. In suchembodiments, the manual delivery vehicle operator may select a pathbetween each of the deliveries along the delivery route. However, incertain embodiments, the established manual delivery vehicle route mayidentifying a manual delivery vehicle travel path establishing anexpected path between the various established manual delivery vehiclestops along the manual delivery vehicle route.

As indicated at Block 603, the method comprises steps for determiningone or more autonomous-vehicle delivery time radii surrounding eachautonomous delivery destination serviceable point. The autonomousdelivery destination serviceable points are the destination locationscorresponding to each of the autonomous-delivery eligibleshipments/items identified in the steps discussed at Block 601. Forexample, the dashed circles shown in FIGS. 7-9 represent the boundariesof geographic areas within respective autonomous-vehicle delivery timeradii relating to residence 1000 f (shown shaded for emphasis relativeto other potential delivery serviceable points). As shown in FIGS. 7-9,each autonomous delivery destination serviceable point may be associatedwith a plurality of autonomous-vehicle delivery time radii, eachrepresenting a different estimated time for the autonomous delivery tocomplete an autonomous delivery from a manual delivery vehicle 100positioned at the boundary of the geographical area. For example,boundary 1050 a may be representative of an estimated autonomousdelivery time of 10 minutes, and boundary 1050 b may be representativeof an estimated autonomous delivery time of 20 minutes. Although twoboundaries are shown in FIGS. 7-9, it should be understood that anynumber of boundaries may be established for various autonomous deliverydestinations.

In various embodiments, the autonomous-vehicle delivery time radii maybe established independently for each autonomous delivery serviceablepoint (e.g., based on historical information/data indicative of anelapsed amount of time to complete autonomous deliveries from manualdelivery vehicles 100 positioned at various distances away from theautonomous delivery serviceable point). However, in certain embodiments,the autonomous-vehicle delivery time radii may be established based onstandardized distances away from the autonomous delivery serviceablepoint. For example, the standardized distances may be established basedon an estimated time for the autonomous vehicle 140 to travel thestandardized distance, to deposit a shipment/item at a destinationserviceable point, and to travel the standardized distance again, backto the manual delivery vehicle 100.

With reference again to FIGS. 6-9, the autonomous-delivery time radiiare compared against a delivery route (shown as line 790 in FIGS. 6-9)to determine an estimated amount of time that the delivery vehicle islikely to remain within the boundaries of the autonomous-delivery timeradii, as indicated at Blocks 604-610. FIGS. 7-9 provide illustrativeschematics of various steps performed as indicated at Blocks 605-610.

In each of FIGS. 7-9, the delivery route proceeds along First St., alongthe entire length of Second St., and then onto Main St. The manualdelivery vehicle 100 delivers to various manual delivery serviceablepoints (indicated with a “Y” indication) along the manual deliveryvehicle route. In each of FIGS. 7-9, residence 1000 f is indicated asautonomous delivery eligible (indicated by the “D” indication and thegrey shading), and residence 1000 f is associated with two autonomousdelivery radii, 1050 a and 1050 b. For purposes of discussion,autonomous delivery radii 1050 a is associated with a minimum presencetime of 10 minutes to permit autonomous delivery to residence 1000 f;autonomous delivery radii 1050 b is associated with a minimum presencetime of 20 minutes to permit autonomous delivery to residence 1000 f;and it is assumed that manual deliveries at residences (e.g., any ofresidences 1000 a-1000 o) takes 6 minutes.

FIG. 7 illustrates a scenario in which autonomous delivery is availablebased on the estimated amount of time that the manual delivery vehicle100 will be positioned within delivery radii 1050 a. As shown in FIG. 7,the manual delivery vehicle 100 is scheduled to make deliveries atresidences 1000 a, 1000 i, and 1000 j. Because residences 1000 i and1000 j are located within delivery radius 1050 a (with a minimumpresence time of 10 minutes), and each manual delivery is estimated torequire 6 elapsed minutes (for a total cumulative time within radius1050 a of at least 12 minutes), autonomous delivery to residence 1000 fis permitted. Following the Blocks shown in FIG. 6, a mapping computingentity 110 reviewing the delivery route would determine that there is atleast one delivery within the autonomous-delivery radius, as indicatedat Block 605, at Block 607 the mapping computing entity 110 woulddetermine that the estimated time to deliver a shipment/item at thesingle serviceable point (6 minutes) is less than the minimum presencetime. At Block 609, the mapping computing entity 110 would determinethat there is more than 1 delivery scheduled within radius 1050 a(deliveries at residences 1000 i and 1000 j). At Block 610, the mappingcomputing entity 110 would determine that the cumulative estimateddelivery time (12 minutes) is greater than the minimum presence time (10minutes) and the mapping computing entity 110 would set the autonomousvehicle launch location as the first delivery serviceable pointapproached by the manual delivery vehicle 100 that is positioned withinradius 1050 a, as indicated at Block 608. In the case of FIG. 7, theautonomous vehicle 140 would launch from the manual delivery vehicle 100when the manual delivery vehicle 100 reached residence 1000 i. Theautonomous vehicle 140 would be expected to complete the autonomousdelivery to residence 1000 f before the manual delivery vehicle 100completes both deliveries to residences 1000 i and 1000 j.

FIG. 8 illustrates a scenario in which autonomous delivery is notavailable to residence 1000 f because the manual delivery vehicle 100 isnot expected to remain within either distance radii 1050 a, 1050 b forat least the minimum presence time. In the illustrated embodiment ofFIG. 8, the only manual delivery serviceable point along the manualdelivery vehicle route 790 that is within either radii 1050 a, 1050 b isa delivery to residence 1000 j. Because the estimated delivery time toresidence 1000 j (6 minutes) is less than the minimum presence time forradius 1050 a (10 minutes) and for radius 1050 b (20 minutes),autonomous delivery may not be available for a shipment/item to bedelivered to residence 1000 f.

Describing the scenario of FIG. 8 in reference to the steps of FIG. 6,the mapping computing entity 110 may begin by first reviewing deliveryeligibility under the smallest radius (e.g., corresponding to boundary1050 a), and then may repeat the various analytical processes forincreasingly large distance radii upon a determination that autonomousdelivery eligibility is not established. Accordingly, at Block 605, themapping computing entity 110 would determine that there is at least oneautonomous delivery within boundary 1050 a (residence 1000 j), however,at Block 607 the mapping computing entity 110 would determine that theestimated delivery time at the at least one delivery is less than theminimum presence time for the manual delivery vehicle 100 within theboundary 1050 a (estimated delivery time of 6 minutes, versus a minimumpresence time of 10 minutes). At Block 609, the mapping computing entity110 would determine that no other manual deliveries scheduled within thearea bounded by boundary 1050 a. Although not shown in FIG. 6, themapping computing entity 110 may then repeat the analysis represented byBlocks 605-610 with respect to the larger radius corresponding toboundary 1050 b. However, there would be no additional deliveries withinthe area bounded by 1050 b, and so the mapping computing entity 110would then reclassify the delivery to residence 1000 f as a manualdelivery, as indicated at Block 606. Because this is added as a newmanual delivery vehicle stop, the mapping computing entity 110 wouldproceed to generate a new manual delivery vehicle route incorporating astop at residence 1000 f, as indicated at Block 602.

FIG. 9 illustrates a scenario in which autonomous delivery is availableto residence 1000 f based on the amount of time that the manual deliveryvehicle 100 is estimated to remain within the large area bounded by 1050b while traveling along the manual delivery vehicle route 791. In theillustrated embodiment of FIG. 9, the only delivery along the manualdelivery vehicle route 791 that is within the area bounded by boundary1050 a is to residence 1000 j. The estimated delivery time at residence1000 j (6 minutes) is less than the minimum presence time withinboundary 1050 a (10 minutes), and accordingly autonomous delivery toresidence 1000 f is not available based on the presence of the manualdelivery vehicle 100 within boundary 1050 a. However, there areestimated deliveries to residences 1000 j, 10001, 1000 g, and 1000 dwithin the area bounded by 1050 b, for a total estimated delivery timeof 24 minutes (6 minutes for each delivery) within the area bounded by1050 b. This total estimated delivery time is greater than the minimumpresence time for the area within boundary 1050 b (20 minutes), andaccordingly autonomous delivery is available for a shipment/itemdestined to residence 1000 f As noted in FIG. 9, the delivery route forthe manual delivery vehicle 100 passes out of the area bounded by 1050 bwhile the delivery vehicle travels along Main Street, although themanual delivery vehicle 100 passes into the area bounded by 1050 b whilemaking deliveries to residences 1000 g and 1000 d. In variousembodiments, determining whether a manual delivery vehicle 100 isestimated to remain within a radius distance for at least a minimumpresence time may comprise summing the total estimated amount of timethe manual delivery vehicle 100 is expected to remain within the radiusdistance, regardless of whether the manual delivery vehicle 100temporarily leaves the bounded area. In other words, the total presencetime within the bounded area need not be continuous. However, in certainembodiments, each time the manual delivery vehicle 100 leaves thebounded area, the total presence time may reset, and accordingly thetotal presence time for the vehicle within a bounded area may be thetotal continuous presence time for the vehicle within the bounded area.In such an embodiment, the scenario shown in FIG. 9 would not enableautonomous delivery to residence 1000 f.

With reference again to FIG. 6, the scenario shown in FIG. 9 would berepresented by the following computing entity determinations. Themapping computing entity 110 would first proceed through Blocks 605-610with respect to boundary 1050 a, and would determine that autonomousdelivery is not eligible based on manual deliveries within boundary 1050a (the only delivery within boundary 1050 a is at residence 1000 j). Themapping computing entity 110 would then repeat the analysis of Blocks605-610 with respect to boundary 1050 b. With respect to boundary 1050b, the mapping computing entity 110 would determine that there is atleast one delivery within boundary 1050 b (for example, at residence10001), as shown at Block 605. At Block 607, the mapping computingentity 110 would determine that the estimated delivery time at residence10001 (6 minutes) is less than the minimum presence time (20 minutes)within boundary 1050 b. At Block 609, the mapping computing entity 110would determine that additional deliveries are scheduled within boundary1050 b (e.g., deliveries at residences 10001, 1000 j, 1000 g, and 1000d). At Block 610, the mapping computing entity 110 would determine thatthe cumulative estimated delivery time for all of the deliveries (24minutes) is greater than the minimum presence time (20 minutes).Accordingly, at Block 608 the mapping computing entity 110 sets theautonomous delivery launch location as residence 10001 (the firstdelivery within boundary 1050 b).

For purposes of simplicity of explanation the forgoing discussionassumed that the manual delivery vehicle 100 is only present within adistance radius during the period of time that the manual deliveryvehicle 100 is located at a scheduled delivery stop. However, it shouldbe understood that in various embodiments, the travel time that themanual delivery vehicle 100 is moving within the radius (e.g., betweendelivery serviceable points), inclusive of travel delays (e.g., stops toturn across traffic, stops at traffic signals, and/or the like) may beconsidered when determining whether a manual delivery vehicle 100 isestimated to be present within a radius for at least the correspondingminimum presence time.

Moreover, in various embodiments, the launch location for an autonomousvehicle 140 may be set to any of a variety of locations within a radiusarea. For example, the launch location may be the location where themanual delivery vehicle 100 crosses into the radius area (e.g., at thetime and location where the manual delivery vehicle 100 crosses into theradius area). With respect to FIG. 7 as an example, the launch locationmay be set to be immediately before the manual delivery vehicle 100makes a right turn to follow the direction of travel of Second Street.Such embodiments are particularly available in embodiments in which theautonomous vehicle 140 is capable of launching from the manual deliveryvehicle 100 while the manual delivery vehicle 100 is moving.

In certain embodiments, a determination of whether the manual deliveryvehicle 100 is to be located within an autonomous delivery eligibilityradius may be determined in real-time, by comparing a mappedrepresentation of the manual delivery vehicle route against one or moreboundaries, as illustrated in FIGS. 7-9. However, as discussed herein,various embodiments may determine whether a particular deliveryserviceable point is eligible for autonomous delivery based on linkeddelivery serviceable points stored within a serviceable point profilefor the autonomous delivery serviceable point. For example, FIG. 10provides an example of information/data stored within a serviceablepoint profile for residence 1000 f that may be utilized to determinewhether autonomous delivery is available. As shown in FIG. 10, theserviceable point profile may comprise information/data identifying theone or more linked delivery serviceable points located within autonomousdelivery ranges (e.g., corresponding to boundaries 1050 a, 1050 b ofFIGS. 7-9). Accordingly, a determination of whether autonomous deliveryto the serviceable point (e.g., Residence 1000 o), may comprise queryingthe item detail database to determine whether shipments/items arescheduled to be delivered to any of the one or more linked serviceablepoints, and then determining whether the cumulative delivery time forthe one or more shipments/items satisfies an applicable minimum presencetime. With reference to the scenario shown in FIG. 7, autonomousdelivery eligibility for deliveries to Residence 1000 f may bedetermined by querying the serviceable point profile corresponding toResidence 1000 f (as shown in FIG. 10) to identify linked serviceablepoints within boundaries 1050 a, 1050 b. A mapping computing entity 110may be configured to determine that Residences 1000 e, 1000 i, and 1000j are within boundary 1050 a based on the information/data stored in theserviceable point profile for Residence 1000 f. Accordingly, the mappingcomputing entity 110 may then query the item detail database todetermine whether shipments/items are scheduled for manual delivery toany of Residences 1000 e, 1000 i, and/or 1000 j. In the scenario shownin FIG. 7, the mapping computing entity 110 may be configured todetermine that deliveries are scheduled to Residences 1000 i and 1000 j.Accordingly based on the information/data stored within the serviceablepoint profile (e.g., as shown in FIG. 10), the mapping computing entity110 may determine that the manual delivery vehicle 100 is estimated toremain within boundary 1050 a for at least the minimum presence time(e.g., 10 minutes) based on the cumulative delivery time for deliveriesto Residences 1000 i and 1000 j (e.g., 12 minutes). Accordingly,autonomous delivery to Residence 1000 f is available.

B. Determining Autonomous Delivery Eligibility based on Manual DeliveryDestination Serviceable Points

In various embodiments, determining whether one or more items may bedelivered autonomously may be based at least in part on the location ofthe prospective autonomous delivery serviceable point relative to thelocation of a manual delivery serviceable point identified as anautonomous vehicle launch location. As discussed in reference to FIGS.11-12, autonomous delivery eligibility may be established for autonomousdelivery destinations if an autonomous delivery serviceable point iswithin a defined distance (e.g., linear distance) of a particular manualdelivery serviceable point identified as an autonomous vehicle launchlocation. For example, delivery serviceable points having an extendedestimated elapsed delivery time may be identified as potentialautonomous vehicle launch locations, because the manual delivery vehicle100 is expected to remain stationary for an extended period of time,permitting autonomous deliveries to depart from the manual deliveryvehicle 100, deliver a shipment/item at an autonomous deliveryserviceable point, and return to the manual delivery vehicle 100 whilethe manual delivery vehicle 100 remains located at the manual deliveryserviceable point.

Establishing a particular manual delivery serviceable point as a launchlocation may be done dynamically and in real-time, based on theestimated elapsed delivery time at a particular serviceable point. Forexample, after establishing a manual delivery vehicle 100 route, theestimated elapsed delivery time for each manual delivery serviceablepoint may be compared against a launch location criteria to determinewhether the manual delivery serviceable point may be considered a launchlocation for the particular delivery route. For example, the launchlocation criteria may specify a threshold estimated elapsed deliverytime (e.g., a minimum estimated elapsed delivery time) for a particularmanual delivery serviceable point to be considered a launch location.

Alternatively, various manual delivery serviceable points may bepre-selected as autonomous vehicle launch locations. Such manualdelivery serviceable points may be pre-selected based on historicalinformation/data indicating that the manual delivery serviceable pointshave historically had an extended average elapsed delivery time whenmaking deliveries to the manual delivery serviceable point. For example,based on retrieved historical data, a mapping computing entity 110 maybe configured to determine that the average elapsed delivery time for aparticular manual delivery serviceable point satisfies launch locationcriteria (e.g., specifying a threshold (e.g., minimum) estimated elapseddelivery time). As examples, deliveries to large office buildings,apartment buildings, condominium buildings, and/or the like may bedetermined to satisfy applicable launch location criteria.

In certain embodiments, the defined distance for autonomous deliveriesfrom a particular manual delivery serviceable point may be defined foreach manual delivery serviceable point individually. For example, thedefined distance for a first apartment building may be larger than thedefined distance for a second office building. In such embodiments, theestimated elapsed delivery time for the first apartment building may belonger than the estimated elapsed delivery time for the second officebuilding, and accordingly the amount of time that one or more autonomousvehicles 140 may be away from the manual delivery vehicle 100 may belonger while the manual delivery vehicle 100 is located at the firstapartment building than the second office building. However, it shouldbe understood that in certain embodiments, a defined distance forautonomous deliveries may be universally applied to all identifiedlaunch locations (e.g., a defined distance of 1 mile may be utilized forall launch locations), and such a defined distance may be based at leastin part on a travel range of the autonomous vehicles 140.

Moreover, the defined distance for each launch location may beestablished dynamically, for example based on the estimated elapseddelivery time for deliveries to a particular manual delivery serviceablepoint during an established delivery route. Upon establishing a deliveryroute, inclusive of deliveries to a manual delivery destinationidentified as a launch location, a mapping computing entity 110 maydetermine the estimated elapsed delivery time at the identified launchlocation, and may dynamically establish the defined distance based onthe estimated elapsed delivery time. For example, the defined distancemay be established as the maximum distance that an autonomous vehicle140 can travel away from the manual delivery vehicle 100 to complete anautonomous delivery and still return to the manual delivery vehicle 100before the expiration of the estimated elapsed delivery time at themanual delivery serviceable point. However, it should be understood thatthe defined distance for each launch location may be pre-established foreach launch location, and may not be dependent on expected deliveries tothe manual delivery serviceable point. For example, the defined distancefor a first apartment building may be set to be 1.5 miles, regardless ofthe number of deliveries made to the first apartment building during aparticular delivery route.

FIG. 11 is a flowchart showing an example method for determining whetherautonomous delivery is available for various shipments/items, and FIG.12 provides a schematic illustration of a scenario in which autonomousdelivery is available according to the methodology of FIG. 11.

As shown at Block 901 of FIG. 11, an example method for establishingautonomous delivery eligibility begins by identifying manual deliveryserviceable points deemed to be potential launch locations. As notedherein, launch locations may be pre-established, and accordingly variousserviceable points may be identified as launch locations for a vehicleroute (e.g., a serviceable point profile corresponding to a particularserviceable point may identify that the serviceable point is a launchlocation). However, as noted above, launch locations may be determineddynamically, based on a determination that a manual delivery vehicle 100is estimated to remain at a particular manual delivery serviceable pointfor more than a threshold amount of time, thereby enabling autonomousdeliveries to be completed while the manual delivery vehicle 100 remainsat the manual delivery serviceable point.

As indicated at Block 902, autonomous-delivery eligible shipments/itemsare identified that are scheduled to be delivered during a particularvehicle route. As noted above, the autonomous-delivery eligibleshipments/items may be indicated as being autonomous-delivery eligiblein a shipment/item profile corresponding to the shipment/item.

As noted at Block 903, various embodiments comprise steps forestablishing a delivery route for the manual-deliveries. Such a manualdelivery vehicle route may be established according to the methodologydiscussed in reference to FIG. 6, above. Although shown as occurringafter Blocks 901 and 902, it should be understood that the stepsreflected by Blocks 901-903 may be performed in any order.

With reference to FIGS. 11-12, the location of the identifiedautonomous-delivery eligible shipments/items may be compared against oneor more delivery radius surrounding the one or more identified launchlocations to determine whether autonomous delivery from the launchlocations may be completed to the autonomous-delivery eligible deliveryserviceable points.

For example, in the scenario shown schematically in FIG. 12, a manualdelivery vehicle 100 traversing delivery route 1290 makes delivery stopsat a plurality of residences 1000 a-o, shops 1100 a-c, and officebuildings 1200 a-b (e.g., those indicated with a “Y” to reflect ascheduled manual delivery stop). Of particular relevance, officebuilding 1200 b (shaded in grey for emphasis) has been indicated as alaunch location for autonomous deliveries. As noted above, officebuilding 1200 b may have been pre-established as a launch location, oroffice building 1200 b may have been established as a launch locationresponsive to determining that the manual delivery vehicle 100 isestimated to be located at the office building 1200 b for at least athreshold amount of time to enable autonomous deliveries while themanual delivery vehicle 100 remains at the office building 1200 b.

As shown in FIG. 12, office building 1200 b may be associated with anautonomous delivery range indicated by boundary 1250. As mentionedherein, the autonomous delivery range may be pre-established for officebuilding 1200 b, or the autonomous delivery range may be establisheddynamically, for example, based at least in part on an estimated elapsedtime to complete the manual deliveries at the office building 1200 b.

In the scenario of FIG. 12, comparing the destination serviceable pointfor various autonomous-delivery eligible shipments/items (Residences1000 d, 1000 k, and 1000 o; as indicated by the “D” indicatorcorresponding to each residence) as indicated at Blocks 904-905 of FIG.11, indicates that only Residences 1000 k and 1000 o are within theautonomous-delivery eligible radius of office building 1200 b.Accordingly, the autonomous-delivery eligible shipment/item destined forResidence 1000 d is reclassified as a manual delivery shipment/item, asindicated at Block 907, and the delivery route is updated to reflect thestop at Residence 1000 d, as indicated at Block 903.

With respect to Residences 1000 k and 1000 o, the mapping computingentity 110 may determine that these residences are within theautonomous-delivery eligible range of office building 1200 b, andaccordingly the mapping computing entity 110 may establish officebuilding 1200 b as the launch location for autonomous deliveries to eachof Residences 1000 k and 1000 o, as shown at Block 906.

In certain embodiments, a determination of whether autonomous deliverymay be completed to a particular destination serviceable point may bedetermined in real-time, by comparing a mapped representation of theautonomous delivery serviceable points against various launch locations,as illustrated in FIG. 12. However, as discussed herein, variousembodiments may determine whether a particular delivery serviceablepoint is eligible for autonomous delivery based on linked deliveryserviceable points stored within a serviceable point profile for theidentified launch location. For example, FIG. 13 provides an example ofinformation/data stored within a serviceable point profile for officebuilding 1200 b that may be utilized to determine whether autonomousdelivery is available for one or more shipments/items to be delivered tolocations surrounding office building 1200 b. As shown in FIG. 13, theserviceable point profile may comprise information/data identifying theone or more linked delivery serviceable points located within autonomousdelivery range (e.g., corresponding to boundary 1250 of FIG. 12).Accordingly, a determination of whether autonomous delivery to aparticular serviceable point is available may comprise querying theserviceable point profile database based on information/data identifyinga destination serviceable point for a particular shipment/item todetermine whether the destination serviceable point is stored as alinked serviceable point to one or more launch locations. With referenceto the scenario shown in FIG. 12, upon receipt of information/dataindicating that shipments/items to residences 1000 d, 1000 k, and 1000 oare eligible for autonomous delivery, the mapping computing entity 110may be configured to query the serviceable point profile database todetermine whether any of residences 1000 d, 1000 k, and/or 1000 o areidentified as linked serviceable points located within an autonomousdelivery range of an identified launch location and identified withinthe serviceable point profile corresponding to the identified launchlocation. Accordingly, the mapping computing entity 110 would retrievethe serviceable point profile corresponding to the office building 1200b (e.g., based on the results of a query for serviceable point profilesidentifying one or more of residences 1000 d, 1000 k, and/or 1000 o aslinked serviceable points and would determine that only residences 1000k and 1000 o are located within an autonomous delivery range of officebuilding 1200 b. Responsive to determining that residence 1000 d is notidentified as a linked serviceable point within other serviceable pointprofiles corresponding to launch locations, the delivery to residence1000 d is reclassified as a manual delivery shipment/item.

Although not shown in any of FIGS. 11-13, in various embodiments aparticular launch location may be associated with an autonomous deliverylimit establishing a maximum number of autonomous deliveries that may bemade while the manual delivery vehicle 100 is located at the launchlocation. The autonomous delivery limit may be pre-established for aparticular launch location, and may be stored in the serviceable pointprofile for the launch location. In certain embodiments, the autonomousdelivery limit may comprise a plurality of autonomous delivery limits,each of which provide an autonomous delivery limit based on the numberof autonomous vehicles 140 carried by a particular manual deliveryvehicle 100. For example, the autonomous vehicle limit for a particularapartment building may set a first maximum number of autonomousdeliveries to 6 for manual delivery vehicles 100 carrying 3 autonomousvehicles 140; and a second maximum number of autonomous deliveries to 12for manual delivery vehicles 100 carrying 6 autonomous vehicles 140.

C. Determining Autonomous Delivery Eligibility Based on Geofences

In various embodiments, determining whether one or more items may bedelivered autonomously may be based at least in part on the location ofthe prospective autonomous delivery serviceable point relative to adefined geofenced area. As discussed in reference to FIGS. 14-15,autonomous delivery eligibility may be established for autonomousdelivery destinations if an autonomous delivery serviceable point ispositioned within a geofenced area satisfying a geofence-deliverycriteria. For example, if the autonomous delivery serviceable point ispositioned within a geofence comprising a threshold (e.g., minimum)number of manual delivery serviceable points along a vehicle route, thenthe autonomous delivery serviceable point is eligible for autonomousdelivery. As a specific example, a particular geofence may be definedaround a neighborhood comprising a plurality of residences, around aparticular zip code, around a particular town, around a particularsubsection of a neighborhood, and/or the like.

In certain embodiments, a mapping computing entity 110 may be configuredto automatically generate a geofence to encompass a plurality ofdelivery serviceable points. For example, a geofence may beautomatically generated in response to user input indicating that aplurality of delivery serviceable points should be grouped within thedefined geofence. Upon receipt of such user input, the mapping computingentity 110 may be configured to automatically determine the location ofboundaries of a geofence to encompass the identified deliveryserviceable points, for example, based on location information/datastored in serviceable point profiles corresponding to the identifieddelivery serviceable points.

In certain embodiments, the mapping computing entity 110 may beconfigured to store information/data indicative of a plurality ofgeofenced areas in association with corresponding cluster profiles. Eachcluster profile may be stored in a cluster profile database and maycomprise information/data identifying those serviceable points within acommon geofenced area. For example, all those serviceable pointsdetermined to be within a single geofenced area may be identified to bewithin a single cluster associated with a corresponding cluster profile.

In certain embodiments, the inclusion of a serviceable point within aparticular geofenced area may be identified according toinformation/data stored in serviceable point profiles. For example, eachserviceable point profile may comprise a cluster-identifier field havinga unique identifier corresponding to the cluster stored therein. Toidentify serviceable points within a common cluster, the serviceablepoint profile database may be queried to compile a listing of all thoseserviceable points sharing a common cluster identifier.

Alternatively, each serviceable point profile may identify each otherserviceable point within a common cluster as linked serviceable pointswithin the serviceable point profile. FIG. 16 illustrates exampleinformation/data that may be stored in a serviceable point profile for aserviceable point within a cluster of serviceable points, according toone embodiment. As shown in FIG. 16, the serviceable point profile maycomprise a cluster identifier field and a listing of linked serviceablepoints within the same cluster. However, as noted above, a serviceablepoint profile may comprise only one of (1) the cluster identifier fieldor (2) the listing of linked serviceable points within the same cluster.

As indicated in FIGS. 14-15, the mapping computing entity 110 may beconfigured to determine whether autonomous delivery is available for oneor more autonomous-delivery eligible shipments/items. Specifically, FIG.14 is a flowchart showing an example method for determining whetherautonomous delivery is available for various shipments/items, and FIG.15 provides a schematic illustration of a scenario in which autonomousdelivery is available according to the methodology of FIG. 14.

As shown at Block 951 of FIG. 14, an example method for establishingautonomous delivery eligibility begins by identifying geofenced areasidentified as autonomous-delivery eligible. For example, variousneighborhoods may be identified as autonomous delivery eligible, suchthat various shipments/items destined for delivery to locations withinthe neighborhood may be delivered autonomously while othershipments/items destined for delivery to locations within theneighborhood are delivered manually.

Upon identifying a geofenced area identified as autonomous-deliveryeligible, the mapping computing entity 110 is configured to identify oneor more autonomous-delivery eligible shipments/items destined fordelivery to locations within the identified geofenced area, as indicatedat Block 952. As noted above, the autonomous-delivery eligibleshipments/items may be indicated as being autonomous-delivery eligiblein a shipment/item profile corresponding to the shipment/item.

As noted at Block 953, various embodiments comprise steps forestablishing a delivery route for manual deliveries. Such a manualdelivery vehicle route may be established according to the methodologydiscussed in reference to FIG. 6, above. Although shown as occurringafter Blocks 951 and 952, it should be understood that the stepsreflected by Blocks 951-953 may be performed in any order.

With reference to FIGS. 14-15, the established manual delivery vehicleroute 1590 and the one or more autonomous-delivery eligibleshipments/items may be compared against geofence-delivery criteria todetermine whether autonomous delivery is available for one or moreshipments/items. For example, the geofence-delivery criteria may specifya minimum number of manual deliveries within the geofenced area toenable autonomous delivery of various shipments/items. In certainembodiments, the minimum number of manual deliveries may specify theoverall minimum number of manual deliveries for any number of autonomousdeliveries. For example, the geofence-delivery criteria may indicatethat there must be at least three manual deliveries scheduled within thegeofenced area for autonomous delivery to be available for anyshipments/items. In certain embodiments however, the minimum number ofmanual deliveries may specify a minimum number of manual deliveries foreach scheduled autonomous delivery within the geofenced area. Forexample, the geofence-delivery criteria may indicate that there must beat least two manual deliveries scheduled within the geofenced area foreach autonomous delivery scheduled within the geofenced area. As a morespecific example, to deliver one shipment/item autonomously within thegeofenced area, there must be at least two scheduled manual deliverieswithin the geofenced area. By extension to delivery two shipments/itemsautonomously, there must be four manual deliveries within the samegeographical area.

As yet another example, the geofence-delivery criteria may specify aminimum estimated presence time for the manual delivery vehicle 100 tobe located within the geofenced area. The estimated presence time may bedetermined based on an estimated elapsed delivery time at each manualdelivery serviceable point within the geofenced area. In certainembodiments, the estimated presence time may comprise the cumulativeestimated delivery time at each of the manual delivery serviceablepoints, the estimated travel time for the manual delivery vehicle 100within the geofenced area, and/or the like.

In certain embodiments, the geofence-delivery criteria may beestablished for each geofenced area independently. For example, a firstgeofenced area may have a first set of geofence-delivery criteriaassociated therewith, and a second geofenced area may have a second setof geofence-delivery criteria associated therewith.

With reference to the scenario illustrated in FIG. 9, initially assumethe geofence-delivery criteria specifies an absolute minimum number ofmanual deliveries required for any number of autonomous deliverieswithin the same geofenced area. For purposes of discussion, assume thedefined minimum number of manual deliveries is 4. Accordingly, becausethere are 4 scheduled manual deliveries within the geofenced area (atResidences 1000 i, 1000 j, 1000 g, and 1000 h; indicated with the “Y”indicator on each), the geofence-delivery criteria is determined to besatisfied, as indicated at Block 955 of FIG. 14. Accordingly,autonomous-delivery is available to all 3 autonomous-delivery eligibleserviceable points (Residences 1000 e, 1000 k, and 1000 o; indicatedwith the “D” indicator and shaded for emphasis). Thus, as indicated atBlock 956 of FIG. 14, the mapping computing entity 110 would set theautonomous vehicle launch location as the first delivery serviceablepoint approached by the manual delivery vehicle 100 that is positionedwithin geofenced area 1060 (i.e., Residence 1000 i in the scenarioillustrated in FIG. 15). As discussed in reference to FIG. 6, the launchlocation for the autonomous vehicle 140 may be set to any of a varietyof locations, such as the location where the manual delivery vehicle 100first crosses into geofenced area 1060. The autonomous vehicle(s) 140would be expected to complete all of the autonomous deliveries beforethe manual delivery vehicle 100 completes all of the manual deliverieswithin the same geofenced area 1060.

Again with reference to FIG. 9, now assume the geofence-deliverycriteria specifies a minimum number of manual deliveries required foreach autonomous delivery within the geofenced area. For purposes ofdiscussion, assume the defined minimum number of manual deliveries foreach autonomous delivery is 2. Accordingly, because there are 4scheduled manual deliveries within the geofenced area 1060, only 2autonomous deliveries may be completed. As discussed in greater detailherein, the mapping computing entity 110 may utilize any of a variety ofmethodologies for resolving autonomous delivery conflicts to determinewhich autonomous-delivery eligible shipment/item should be reclassifiedas a manual delivery shipment/item. For example, because reclassifyingthe delivery to Residence 1000 k as a manual delivery would not requirea change to the manual delivery vehicle route, the mapping computingentity 110 may reclassify the delivery to Residence 1000 k as a manualdelivery, as indicated at Block 957. As indicated in the prior example,the mapping computing entity 110 would set the autonomous vehicle launchlocation as the first delivery serviceable point approached by themanual delivery vehicle 100 that is positioned within geofenced area1060 (i.e., Residence 1000 i in the scenario illustrated in FIG. 15) forautonomous deliveries to Residences 1000 e and 1000 o. As discussed inreference to FIG. 6, the launch location for the autonomous vehicle 140may be set to any of a variety of locations, such as the location wherethe manual delivery vehicle 100 first crosses into geofenced area 1060.The autonomous vehicle(s) 140 would be expected to complete all of theautonomous deliveries before the manual delivery vehicle 100 completesall of the manual deliveries within the same geofenced area 1060.

In certain embodiments, a determination of whether the manual deliveryvehicle 100 will satisfy the geofence-delivery criteria may be made inreal-time, by comparing a mapped representation of the manual deliveryvehicle route (inclusive of scheduled stops) against the boundaries of ageofenced area, as illustrated in FIG. 15. However, as discussed herein,various embodiments may determine whether one or more deliveryserviceable points are eligible for autonomous delivery based on linkeddelivery serviceable points stored within a serviceable point profile,based on delivery serviceable points identified within a clusterprofile, and/or the like. As noted above, FIG. 16 provides an example ofinformation/data stored within a serviceable point profile for residence1000 i that may be utilized to determine whether autonomous delivery isavailable to various locations within geofenced area 1060. Accordingly,a determination of whether autonomous delivery for shipments/itemsdestined to various locations within geofenced area 1060 may bedetermined by querying the serviceable point profiles corresponding tovarious locations with the geofenced area 1060 to identify linkedserviceable points within the common geofenced area 1060. The mappingcomputing entity 110 may determine how many of the linked serviceablepoints have corresponding manual deliveries scheduled to theirlocations, and how many of the serviceable points have autonomousdeliveries schedule to their respective locations. The mapping computingentity 110 may then compare the number of manual deliveries (and/or theestimated elapsed time of manual deliveries) and/or the number ofautonomous deliveries against the geofence-delivery criteria todetermine whether autonomous delivery is available for any of theshipments/items, as indicated in FIG. 14.

D. Resolving Autonomous Delivery Eligibility Conflicts

The forgoing methodologies for establishing autonomous deliveryeligibility may result in scenarios in which autonomous delivery to aparticular location may be available from a plurality of launchlocations, and/or the mapping computing entity 110 may be required toselect only a subset of autonomous-delivery eligible shipments/items toreclassify as manual delivery shipments/items. The mapping computingentity 110 may be configured to resolve such conflicts to optimize theoverall delivery activities (inclusive of both manual deliveries andautonomous deliveries) assigned to a particular manual delivery vehicle100. For example, the mapping computing entity 110 may be configured tominimize resource usage by the manual delivery vehicle 100, theautonomous vehicle 140, and/or the like.

1. Selecting One of a Plurality of Possible Launch Locations

In certain embodiments, autonomous delivery may be available to aparticular autonomous delivery serviceable point from a plurality ofpossible launch locations. With reference to FIG. 12, for example, ifboth office buildings 1200 a and 1200 b were indicated as possiblelaunch locations, residence 1000 k may be within an autonomous deliveryrange of both office buildings 1200 a and 1200 b. In order to determinewhich of the possible launch locations should be utilized for autonomousdelivery, the mapping computing entity 110 may apply a delivery criteriahierarchy to select a particular launch location for an autonomousdelivery. The delivery criteria hierarchy may comprise one or morecriteria to be utilized to identify an optimal launch location forautonomous delivery. The criteria may be organized in a descending orderof importance, such that the most-important criteria that resolves anoutstanding conflict is automatically applied to establish an optimallaunch location.

In certain embodiments, the delivery criteria hierarchy may cause themapping computing entity 110 to analyze a plurality of autonomousdelivery conflicts simultaneously to generate an optimal delivery planfor the manual delivery vehicle 100. An example delivery criteriahierarchy is discussed below, although it should be understood that anycriteria or combination of criteria may be utilized to resolveconflicts.

As an example, a delivery criteria hierarchy may consider the criterialisted in the chart below, beginning with the criteria identified ashaving the highest importance, and sequentially considering additionalcriteria having descending importance until the conflict is resolved.

Importance Ranking Criteria 1 Maximizing the total number of autonomousdeliveries. 2 Minimizing the distance travelled by the manual deliveryvehicle along the delivery route. 3 Minimizing the distance travelled bythe autonomous vehicles. 4 Launching from a location having a largerestimated duration. 5 Delivering from an earlier-approached launchlocation. 6 Random selection.

In certain embodiments, launch locations for various shipments/items maybe selected in order to maximize the total number of autonomousdeliveries that may be performed within the confines of applicableautonomous-delivery criteria. For example, the autonomous deliverycriteria may set a maximum number of autonomous deliveries that may beperformed from any one launch location. Accordingly, launch locationsfor particular shipments/items may be delegated between variousshipments/items to maximize the total number of shipments/items that maybe delivered autonomously. As a specific, and simplified example, assumethe maximum number of autonomous deliveries that may be made from aparticular launch location is 1. In such an embodiment, if a firstshipment/item may be delivered autonomously from either a first launchlocation or a second launch location, but a second shipment/item mayonly be delivered autonomously from the second launch location, then themapping computing entity 110 sets the first shipment/item to be launchedat the first launch location, and the second shipment/item to belaunched at the second launch location.

In the event that the criteria for maximizing the total number ofautonomous deliveries does not resolve outstanding conflicts, themapping computing entity 110 may select appropriate launch locations tominimize the total distance travelled by the manual delivery vehicle 100along the delivery route. For example, if autonomous delivery of aparticular shipment/item may be achieved by launching from a firstlaunch location or a second launch location, however launching from thesecond launch location would increase the distance travelled by themanual delivery vehicle 100 along the delivery route to add anadditional manual delivery stop whereas launching from the first launchlocation would require the addition of an additional manual deliveryvehicle route along a portion of the delivery route already scheduled tobe travelled by the manual delivery vehicle 100, then the mappingcomputing entity 110 assigns the first launch location to theshipment/item.

In the event that the criteria for minimizing the distance travelled bythe manual delivery vehicle 100 does not resolve outstanding conflicts,the mapping computing entity 110 may be configured to identify a launchlocation for one or more shipments/items to minimize the distancetravelled by the autonomous vehicle 140. For example, the mappingcomputing entity 110 may be configured to select the launch locationlocated geographically closer to the intended destination location forthe shipment/item.

In the event that the criteria for minimizing the distance travelled bythe autonomous vehicle 140 does not resolve outstanding conflicts, themapping computing entity 110 may select a launch location correspondingto a manual delivery serviceable point having a longer estimatedduration as the launch location for a particular shipment/item. Forexample, if the manual delivery vehicle 100 is expected to remainstationary at a first manual delivery serviceable point for a longerperiod of time than the expected time the vehicle will remain stationaryat a second manual delivery serviceable point, the mapping computingentity 110 is configured to select the first manual delivery serviceablepoint as the launch location for the shipment/item.

In the event that the criteria for selecting a launch location having anexpected longer duration does not resolve outstanding conflicts, themapping computing entity 110 may select the earliest-in-time launchlocation along the manual delivery vehicle route as the launch locationfor autonomous delivery of a shipment/item.

Finally, as a fail-safe, the mapping computing entity 110 may beconfigured to randomly select a launch location for autonomous deliveryfor a shipment/item in the event none of the other criteria resolveoutstanding conflicts in the selection of a launch location for aparticular shipment/item.

It should be understood that, in certain embodiments, satisfying one ofthe delivery criteria may conceptually conflict with a separate deliverycriteria. For example, maximizing the number of autonomous deliveriesmay cause the manual delivery vehicle 100 to travel a distance greaterthan otherwise possible. In such embodiments, the hierarchical nature ofthe delivery criteria resolves such conflicts, because once a deliverycriteria solves a delivery conflict and selects an appropriate launchlocation for delivering a shipment/item autonomously, the mappingcomputing entity 110 does not further consider lower-ranked (or higherranked) delivery criteria.

2. Selecting One of a Plurality of Autonomous-Delivery EligibleShipments/Items for Reclassification as a Manual Delivery ServiceablePoint.

In certain embodiments, applicable autonomous delivery criteria mayindicate that only a subset of possible autonomous-delivery eligibleshipments/items may actually be delivered autonomously. As indicatedabove, one potential reclassification criteria for identifying which ofa plurality of shipments/items should be reclassified to be manualdelivery eligible may be to identify a shipment/item that is alreadyalong an existing portion of a manual delivery vehicle route. However,certain embodiments may apply a reclassification criteria hierarchy,similar to the delivery criteria hierarchy described above. In variousembodiments, the mapping computing entity 110 may be configured to applycriteria of decreasing identified importance to the plurality ofpossible shipments/items for reclassification until existing conflictsare resolved.

In certain embodiments, the reclassification criteria hierarchy maycause the mapping computing entity 110 to analyze a plurality ofautonomous delivery conflicts simultaneously to generate an optimaldelivery plan for the manual delivery vehicle 100. The reclassificationcriteria may be analyzed in combination (e.g., simultaneously) with thedelivery criteria to create the optimal delivery plan for the manualdelivery vehicle 100, for example to ensure that reclassification ofvarious deliveries does not substantially increase the resourcesrequired to complete a delivery route (e.g., increasing delivery routetime, decreasing number of autonomous deliveries, increasing estimatedmanual delivery vehicle fuel usage, and/or the like). An examplereclassification criteria hierarchy is discussed below, although itshould be understood that any criteria or combination of criteria may beutilized to resolve conflicts.

As an example, a reclassification criteria hierarchy may consider thecriteria listed in the chart below, beginning with the criteriaidentified as having the highest importance, and sequentiallyconsidering additional criteria having descending importance until theconflict is resolved.

Importance Ranking Criteria 1 Maximizing the total number of autonomousdeliveries. 2 Minimizing the distance travelled by the manual deliveryvehicle along the delivery route. 3 Minimizing the distance travelled bythe autonomous vehicles. 4 Providing an autonomous delivery preferenceto delivery locations having identified characteristics. 5 Randomselection. 6 Maximizing the total number of autonomous deliveries.

In certain embodiments, various shipments/items may be selectivelyreassigned for manual delivery to optimize the delivery of a pluralityof shipments/items. For example, reassigning a particular shipment/itemfor manual delivery may result in a change in the route assigned to acorresponding manual delivery vehicle 100 that enables an increase inthe number of shipments/items to be autonomously delivered. As aspecific example, reassigning a shipment/item for manual delivery mayreroute the manual delivery vehicle 100 along a street that would nothave been traveled by the manual delivery vehicle but for thereassignment. That newly traveled street may be nearer to a plurality ofautonomous delivery-eligible delivery serviceable points than anylocation along the prior manual delivery vehicle route, such that agreater number of shipments/items may be delivered autonomously as aresult of the reassignment.

Thus, in instances in which two (or more) manual delivery vehicle routealternatives may be selected, wherein each route alternative results inat least one package being delivered manually and at least one packagebeing delivered autonomously, the mapping computing entity 110 mayutilize the reclassification criteria to select the manual deliveryvehicle route alternative which results in the greatest number ofshipments/items being eligible for autonomous delivery. As noted, thereclassification criteria may be applied after a manual delivery vehicleroute is established (in which case the reclassification criteria maycause a modification to the manual delivery vehicle route) and/or thereclassification criteria may be applied during generation of the manualdelivery vehicle route.

In the event that the reclassification criteria for maximizing the totalnumber of autonomous deliveries does not resolve outstanding conflicts(e.g., for reassigning a subset of a plurality of shipments/items formanual delivery), the mapping computing entity 110 may select identifyone or more shipments/items for reassignment to minimize the totaldistance traveled by the manual delivery vehicle 100 along the deliveryroute. For example, if one autonomous delivery eligible shipmentdestination is located near an existing portion of a manual deliveryvehicle route, and a second autonomous delivery eligible shipmentdestination is located farther away from the existing portion of themanual delivery vehicle route, such that reassigning the secondautonomous delivery eligible shipment/item for manual delivery wouldincrease the distance traveled by the manual delivery vehicle 100, themapping computing entity 110 may be configured to reassign the firstshipment/item for manual delivery, while assigning the secondshipment/item for autonomous delivery.

In the event that the reclassification criteria for minimizing thedistance travelled by the manual delivery vehicle 100 does not resolveoutstanding conflicts for reassigning a subset of a plurality ofshipments/item for manual delivery, the mapping computing entity 110 mayselect one or more shipments/items for reassignment to manual deliveryto minimize the distance travelled by the one or more autonomousvehicles 140. Because the autonomous vehicles 140 may have limitedflight times (e.g., due to limited onboard power supplies), the mappingcomputing entity 110 may reassign one or more shipments/items for manualdelivery to minimize the total distance travelled by the autonomousvehicles 140, thereby minimizing the risk of unanticipated powerfailures while the autonomous vehicles 140 are deliveringshipments/items and are positioned away from the manual delivery vehicle100.

In the event that the reclassification criteria for minimizing thedistance travelled by the autonomous vehicles 140 does not resolveoutstanding conflicts, the mapping computing entity 110 may select oneor more shipments/items for reassignment to manual delivery to provide apreference for autonomous delivery to delivery destinations having oneor more identified characteristics. For example, a delivery destinationmay receive more than a threshold number of shipments/items in a giventime period (e.g., each week), the delivery destination may beassociated with a delivery customer who has paid for premium autonomousdelivery services, the delivery destination may have a favorableautonomous delivery configuration (e.g., minimal airborne obstructions,low crime rates, secure delivery location, predictable landing locationfor the autonomous vehicle 140 at the delivery destination, and/or thelike), and/or the like. In such embodiments, the mapping computingentity 110 may retrieve information/data stored within a deliverydestination profile and/or a customer profile to determine whether aparticular delivery destination satisfies one or more preferencecriteria when reassigning shipments/items for manual delivery.Responsive to determining that a particular destination serviceablepoint and/or customer profile satisfies the preference criteria, themapping computing entity 110 may reassign a different shipment/item formanual delivery such that a shipment/item destined for the deliveryserviceable point determined to satisfy the preference criteria isdelivered autonomously.

Finally, as a fail-safe, the mapping computing entity 110 may beconfigured to randomly select one or more shipments/items forreassignment to manual delivery in the event that none of the othercriteria resolve outstanding conflicts in the selection of ashipment/item to be reassigned. The random selection may be performedaccording to parameters that ensure that the outstanding conflict isresolved by the random selection. For example, the random selection maybe limited to only those shipments/items for which a conflict hasarisen, such that the selection of one or more of the shipments/itemsfor reassignment necessarily resolves the outstanding conflict.

As mentioned above, satisfying one of the reassignment criteria mayconceptually conflict with a separate reassignment criteria. Forexample, maximizing the number of autonomous deliveries may cause themanual delivery vehicle 100 to travel a distance greater than otherwisepossible. In such embodiments, the hierarchical nature of thereassignment criteria resolves such conflicts, because once a deliverycriteria solves a delivery conflict and selects an appropriate launchlocation for delivering a shipment/item autonomously, the mappingcomputing entity 110 does not further consider lower-ranked (or higherranked) delivery criteria.

E. Executing a Delivery Route

Once various shipments/items to be delivered by a particular manualdelivery vehicle 100 have been assigned for autonomous delivery and/ormanual delivery, the mapping computing entity 110 establishes a finaldelivery route (e.g., an ordered listing of deliveries to be performedby a manual delivery vehicle 100 and/or an assigned travel path for themanual delivery vehicle 100, including the location of scheduled stopsfor the manual delivery vehicle 100) and launch locations for one ormore autonomous vehicles 140 to deliver shipments/items between themanual delivery vehicle 100 and the destination serviceable pointcorresponding to the shipments/items. In certain embodiments, the finaldelivery route may be stored in a memory associated with the mappingcomputing entity 110, and/or may be transmitted to an onboard computingentity for the manual delivery vehicle 100, a user computing entity 105carried by the manual delivery vehicle operator, the onboard controlsystem of the autonomous vehicles 140, and/or the like. In certainembodiments, the final delivery route may be viewable via a displayassociated with the computing entity. For example, the computing entitymay be configured to generate a graphical display of a map indicatingthe assigned travel path for the manual delivery vehicle 100, thelocation of various manual delivery stops (e.g., indicated by one ormore icons), the launch location for various autonomous vehicles 140(e.g., indicated by one or more icons), the expected travel path for thevarious autonomous vehicles 140, the destination serviceable points forthe autonomously delivered shipments/items (e.g., indicated by one ormore icons), and/or the like.

In operation, the execution of various delivery (and/or pick-up)processes defined for the delivery route may be based at least in parton the location of the manual delivery vehicle 100 along the assignedmanual delivery route (and/or the location of the manual deliveryvehicle 100 relative to one or more delivery stops included in theordered listing of delivery stops for the manual delivery vehicle 100).As noted, the manual delivery vehicle operator may be informed of theassigned manual delivery vehicle route via one or more computingentities onboard the manual delivery vehicle 100 and/or carried by themanual delivery vehicle operator. The manual delivery vehicle 100 maythen traverse the assigned delivery route to proceed to various manualdelivery serviceable points. As the manual delivery vehicle 100 moves,the onboard computing entity monitors the current location of the manualdelivery vehicle 100 relative to established launch locations for theautonomous vehicles 140. Upon reaching an established launch location(e.g., which may be at a manual delivery serviceable point and/or anypoint along the assigned manual delivery vehicle route), the onboardcomputing entity of the manual delivery vehicle provides signals toonboard launch mechanisms of the manual delivery vehicle 100 and/or tothe onboard control system of the autonomous vehicle 140 to initialize alaunch sequence for the autonomous vehicle 140.

Once the autonomous vehicle 140 has launched from the manual deliveryvehicle 100, the manual delivery vehicle 100 (and/or manual deliveryvehicle operator) continue to perform assigned delivery operations formanual delivery shipments/items. Simultaneously, the autonomous vehicle140 navigates to an assigned destination serviceable point for anautonomous delivery shipment/item, utilizing onboard locationdetermining devices, onboard sensors, and/or the like to travel to thedesired destination serviceable point while avoiding obstacles along theway. Once at the destination serviceable point, the autonomous vehicle140 locates the appropriate delivery location (e.g., via onboardsensors), and deposits the shipment/item at the appropriate deliveryserviceable point (e.g., on a front porch, on a balcony, on a printeddelivery target, and/or the like). Once the autonomous vehicle 140deposits the shipment/item at the delivery serviceable point, theautonomous vehicle 140 returns to the manual delivery vehicle 100. Invarious embodiments, the manual delivery vehicle 100 may have moved to anew location while the autonomous vehicle 140 was delivering theshipment/item, and accordingly the onboard control system of theautonomous vehicle 140 may be in electronic communication with theonboard computing entity of the manual delivery vehicle 100 to ascertainthe current location of the manual delivery vehicle 100. The manualdelivery vehicle 100 may periodically send updated locationinformation/data to the autonomous vehicle 140, such that the autonomousvehicle 140 navigates to the location of the manual delivery vehicle100. Accordingly, even if the manual delivery vehicle 100 is moving, theautonomous vehicle 140 receives continuously updated locationinformation/data for the manual delivery vehicle 100. Once theautonomous vehicle 140 reaches the manual delivery vehicle 100, theautonomous vehicle 140 may land on the manual delivery vehicle 100(e.g., via one or more landing mechanisms of the manual delivery vehicle100). The autonomous vehicle 140 may then be stored in association withthe manual delivery vehicle 100 and/or prepared for a future autonomousdelivery (e.g., at a next assigned launch location).

In certain embodiments, the autonomous vehicle 140 may be configured totransmit location information/data to the manual delivery vehicle 100onboard computing entity, such that the manual delivery vehicle 100onboard computing entity may track the location of each autonomousvehicle 140 relative to the location of the manual delivery vehicle 100.In certain embodiments, the autonomous vehicle 140 may be configured totransmit a mayday alert to the manual delivery vehicle 100 if theautonomous vehicle 140 becomes disabled or trapped during an autonomousdelivery. In such embodiments, the manual delivery vehicle operator maybe informed of the location of the disabled and/or trapped autonomousvehicle 140, such that the manual delivery vehicle operator may deviatefrom a planned delivery route to retrieve the autonomous vehicle 140.

Moreover, in certain embodiments, the manual delivery vehicle 100onboard computing entity may be configured to monitor the location ofthe autonomous vehicle 140 relative to manual delivery vehicle 100 toensure the autonomous vehicle 140 is capable of returning to the manualdelivery vehicle 100 (e.g., based on an estimated travel range of theautonomous vehicle 140). The manual delivery vehicle 100 onboardcomputing entity may be configured to generate an alert responsive todetermining that the manual delivery vehicle 100 is exiting an estimatedtravel range of the autonomous vehicle 140, such that the manualdelivery vehicle operator may stop the manual delivery vehicle 100 toawait the return of the autonomous vehicle 140.

V. CONCLUSION

Many modifications and other embodiments will come to mind to oneskilled in the art to which this disclosure pertains having the benefitof the teachings presented in the foregoing descriptions and theassociated drawings. Therefore, it is to be understood that thedisclosure is not to be limited to the specific embodiments disclosedand that modifications and other embodiments are intended to be includedwithin the scope of the appended claims. Although specific terms areemployed herein, they are used in a generic and descriptive sense onlyand not for purposes of limitation.

In certain embodiments, a computing system determining whetherautonomous delivery is available as discussed herein may be furtherconfigured to modify shipping schedules for various computing entitiesto synchronize deliveries among shipments/items destined for nearbyaddresses, as discussed in co-pending U.S. patent application Ser. No.14/988,136, filed on Jan. 5, 2016, the contents of which is incorporatedherein by reference in its entirety. For example, responsive todetermining that autonomous delivery is unavailable for a shipment/itemduring an originally scheduled delivery date, the computing entity mayquery delivery schedules for adjacent delivery dates (e.g., a datebefore and/or a date after the original delivery date) to determinewhether autonomous delivery would be available for the shipment/item ifdelivered on one of the adjacent delivery dates (e.g., based on thelocation of deliveries along a defined delivery route for the adjacentdelivery dates). Responsive to determining that autonomous deliverywould be available on an adjacent delivery date, the computing entitymay be configured to modify the service level for the shipment/item(e.g., by speeding up shipment/item by increasing shipping level or byslowing down shipment/item by decreasing a shipping level) such that theautonomous delivery eligible item is delivered on the identifiedadjacent delivery date.

1. An autonomous vehicle item delivery method for autonomouslydelivering at least one item to a destination location, the methodcomprising: determining at least one autonomous delivery-eligible itemsatisfies autonomous delivery criteria; identifying at least one manualdelivery location as a launch location for the autonomous vehicle todepart a delivery vehicle for final delivery of the at least oneautonomous delivery-eligible item satisfying the autonomous deliverycriteria to the destination location; and causing the autonomous vehicleto depart from the delivery vehicle to deliver the at least oneautonomous delivery-eligible item satisfying the autonomous deliverycriteria to the destination location.
 2. The method of claim 1, whereinthe launch location is located within a predefined distance of thedestination location for the at least one autonomous delivery-eligibleitem.
 3. The method of claim 1, wherein identifying the at least onemanual delivery location as the launch location comprises identifying alocation IA here the delivery vehicle crosses a radius area of thedestination location.
 4. The method of claim 1, wherein identifying theat least one manual delivery location as the launch location is based ona determination that the delivery vehicle is estimated to remain at aparticular manual delivery serviceable point for more than a thresholdamount of time.
 5. The method of claim 1, wherein the autonomousdelivery criteria comprise a hierarchy of criteria for identifying thelaunch location, the hierarchy of criteria ranked for maximizingdelivery of a total number of autonomous delivery-eligible items.
 6. Themethod of claim 1, wherein identifying the at least one manual deliverylocation as the launch location comprises an analysis of simultaneousconflicts when delivering a plurality of autonomous delivery-eligibleitems.
 7. The method of claim 1, further comprising reclassifying the atleast one autonomous delivery-eligible item as at least one manualdelivery-eligible item.
 8. One or more non-transitory computer storagemedia having computer-executable instructions embodied thereon, thatwhen executed by at least one processor, cause a computer system toperform a method for autonomously delivering at least one item to anautonomous delivery location, the method comprising: receiving item datafor the at least one item; and determining a launch location along amanual delivery vehicle route from a first manual delivery location tothe autonomous delivery location, the determining based at least in parton the item data and one or more established clusters of autonomousdelivery locations, wherein an autonomous vehicle is configured todepart a manual delivery vehicle at the launch location to deliver theat least one item to the autonomous delivery location.
 9. The media ofclaim 8, wherein the one or more established clusters of autonomousdelivery locations comprise serviceable points for autonomous deliverieswithin a single geofenced area.
 10. The media of claim 9, wherein thesingle geofenced area comprises a nuniber above a threshold number ofthe serviceable points along the manual delivery vehicle route.
 11. Themedia of claim 9, wherein the single geofenced area is defined around aneighborhood comprising either a plurality of residences or a particularsubsection of a neighborhood.
 12. The media of claim 8, wherein the oneor more established clusters of autonomous delivery locations aredetermined based on location information of manual delivery locations.13. The media of claim 8, wherein the item data comprises shipmentinstructions for the at least one item.
 14. The media of claim 8,further comprising: prior to determining the launch location,determining a recipient of the at least one item prefers autonomousdelivery to manual delivery; updating the item data based on thedetermining the recipient of the at least one item prefers autonomousdelivery; and prior to determining the launch location, determining theitem data satisfies autonomous delivery criteria.
 15. The media of claim8, further comprising: determining that a recipient of a second itemprefers manual delivery to autonomous delivery; and updating item dataof the second item to indicate that autonomous delivery is not availablefor the second item.
 16. An autonomous vehicle item delivery method forautonomously delivering at least one item to a destination location, themethod comprising: receiving item data for the at least one item; anddynamically establishing a launch location along a manual delivery routebased at least in part on the item data and on an estimated elapseddelivery time for delivering the at least one item to a particularmanual delivery serviceable point along the manual delivery route,wherein the autonomous vehicle is configured to depart a manual deliveryvehicle at the launch location to deliver the at least one item to thedestination location corresponding to the particular manual deliveryserviceable point.
 17. The method of claim 16, further comprising: priorto dynamically establishing the launch location, determining theestimated elapsed delivery time using historical delivery data ofhistorical deliveries to the particular manual delivery serviceablepoint.
 18. The method of claim 17, wherein the historical delivery datacomprises an amount of time for a driver to: unbuckle, disembark fromthe manual delivery vehicle, and return to the manual delivery vehicle.19. The method of claim 16, wherein the item data for the at least oneitem comprises an item size, an item weight, and contents of the item.20. The method of claim 16, wherein the estimated elapsed delivery timewas determined based on an amount of time the manual delivery vehiclewould be positioned within a delivery radius surrounding the particularmanual delivery serviceable point.